50+ Machine Learning (ML) Jobs in Bangalore (Bengaluru) | Machine Learning (ML) Job openings in Bangalore (Bengaluru)

Location: Bangalore

Experience: 3-5 years

Type: Full-time | On-site

Start: Immediate

Why this role exists

Most companies are using LLMs.

Very few are building an advantage from them.

Right now, LLM cost is our largest margin constraint, and model behavior is still too generic to be defensible.

This role exists to:

• Turn LLM usage into a cost-efficient system
• Build compounding intelligence across accounts
• Create a differentiated analysis layer that competitors can’t replicate

What you’ll do

You will not just build models.

You will own the intelligence and cost structure of the platform.

1. Drive down LLM cost dramatically

• Reduce cost per interaction from ₹40 → ₹2 within 6 months
• Implement:
• Model tiering (right model for the right task)
• Caching strategies (semantic + response caching)
• Batching and async processing
• PTU / reserved capacity optimization
• Ensure performance does not degrade while reducing cost

2. Optimize infrastructure spend

• Reduce cloud spend from ₹20L/month → ₹4L/month
• Work across infrastructure layers (Azure / compute / inference)
• Balance:
• Latency
• Cost
• Throughput
• Treat infra as a first-class optimization problem

3. Build the fine-tuning and learning pipeline

• Design systems where:
• Every interaction improves future performance
• Build pipelines for:
• Fine-tuning
• Feedback loops
• Continuous model improvement
• Ensure the 5th customer deployment is structurally better than the 1st

4. Create a differentiated intelligence layer

• Build analysis systems that:
• Extract signals from interactions
• Improve decision-making
• Drive outcome improvements
• Move beyond responses → insight + action

5. Enable new AI-native product categories

• Identify opportunities where:
• AI enables workflows that were not previously possible
• Build foundational ML capabilities to unlock those categories
• Focus on creation, not just efficiency

6. Commoditize LLM usage internally

• Abstract complexity of LLM usage from product teams
• Build internal systems where:
• Cost is predictable
• Performance is consistent
• Make LLM usage a reliable utility layer

What success looks like

• Cost per interaction drops to ₹2 or lower
• Infrastructure spend reduces 5x without performance loss
• Model performance improves with every deployment
• Platform develops a clear intelligence advantage
• New AI-native capabilities become possible due to your systems

Who you are

• You have 3-5 years of experience in ML / applied AI / systems engineering
• You have worked with:
• LLMs
• Inference optimization
• Production ML systems
• You think in:
• Systems
• Trade-offs (cost vs latency vs quality)
• You care about real-world impact, not just model metrics

What will make you stand out

• Experience with:
• LLM optimization (prompting, fine-tuning, distillation)
• Distributed systems or infra-level optimizations
• High-scale inference systems
• Built systems that:
• Reduced cost significantly
• Improved performance over time
• Strong understanding of:
• Caching strategies
• Model routing
• Evaluation frameworks

Why join

• You will directly impact company margins and scalability
• Your work defines whether we have a defensible ML advantage
• You will build systems that move from:
• Generic AI usage → compounding intelligence

What this role is not

• Not research-only
• Not experimentation without production impact
• Not isolated from product and business outcomes

What this role is

• A builder of ML systems at scale
• A driver of cost and performance optimization
• A creator of long-term competitive advantage

One question to self-evaluate

Can you build ML systems that get cheaper, smarter, and more valuable with every interaction?

Want to work on exciting GenAI projects for Fortune 500 companies across multiple sectors? Then read on..

About Company:

CSG is a multi-national company having a presence in 20 countries with 1600+ Engineers. Company works with more than 40 Fortune 500 customers such as Sony, Samsung, ABB, Thyssenkrup, Toyota, Mitsubishi and many more.

Job Description:

We are looking for a talented Generative AI Developer to join our dynamic AI/ML team. This position offers an exciting opportunity to leverage cutting-edge Generative AI (GenAI) technologies to drive innovation to solve real world problems. You will be responsible for developing and optimizing GenAI-based applications, implementing advanced techniques like Retrieval-Augmented Generation (RAG), RIG (Retrieval Interleaved Generation), Agentic Frameworks and vector databases. This is a collaborative role where you will work directly with customers cross-functional teams to design, implement, and optimize AI-driven solutions. Exposure to cloud-native AI platforms such as Amazon Bedrock and Microsoft Azure OpenAI is highly desirable.

Key Responsibilities

Generative AI Application Development:

Design, develop, and deploy GenAI-driven applications to address complex industrial challenges.

Implement Retrieval-Augmented Generation (RAG) and Agentic frameworks

Data Management & Optimization:

Design and optimize document chunking strategies tailored to specific datasets and use cases.

Build, manage, and optimize data embeddings for high-performance similarity searches across vector databases.

Collaboration & Integration:

Work closely with data engineers and scientists to integrate AI solutions into existing pipelines.

Collaborate with cross-functional teams to ensure seamless AI implementation.

Cloud & AI Platform Utilization:

Explore and implement best practices for utilizing cloud-native AI platforms, such as Amazon Bedrock and Azure OpenAI, to enhance solution delivery.

Continuous Learning & Innovation:

Stay updated with the latest trends and emerging technologies in the GenAI and AI/ML fields, ensuring our solutions remain cutting-edge.

Requirements:

The ideal candidate will have strong experience in Generative AI technologies, particularly in the areas of RAG, document chunking, and vector database management. They will be able to quickly adapt to evolving AI frameworks and leverage cloud-native platforms to create efficient, scalable solutions. You will be working in a fast-paced and collaborative environment, where innovation and the ability to learn and grow are key to success.

- 3 to 5 years of overall experience in software development, with 3 years focused on AI/ML.

- Minimum 2 years of experience specifically working with Generative AI (GenAI) technologies.

- Python, PySpark and SQL knowledge is necessary for tasks

- Proven ability to work in a collaborative, fast-paced, and innovative environment.

Technical Skills:

- Generative AI Frameworks & Technologies:

- Expertise in Generative AI frameworks, including prompt engineering, fine-tuning, and few-shot learning.

- Familiarity with frameworks such as T5 (Text-to-Text Transfer Transformation), LangChain, Lang Graph, Open-source tech stalk Ollama, Mistral, DeepSeek.

- Strong knowledge of Retrieval-Augmented Generation (RAG) for combining LLMs with external data retrieval systems.

Data Management:

- Experience in designing chunking strategies for different datasets.

- Expertise in data embedding techniques and experience with vector databases like Pinecone, ChromaDB etc

- Programming & AI/ML Libraries:

- Strong programming skills in Python.

- Experience with AI/ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.

Cloud Platforms & Integration:

- Familiarity with cloud services for AI/ML workloads (AWS, Azure).

- Experience with API integration for AI services and building scalable applications.

- Certifications (Optional but Desirable):

- Certification in AI/ML (e.g., TensorFlow, AWS Certified Machine Learning Specialty).

- Certification or coursework in Generative AI or related technologies.

What You’ll Be Doing:

• Design and develop advanced AI/ML models to solve complex business problems
• Work closely with cross-functional teams including data engineers and domain experts
• Perform exploratory data analysis, data cleaning, and model development
• Translate business challenges into data-driven solutions and actionable insights
• Drive innovation in advanced analytics and AI/ML capabilities
• Communicate model insights effectively to both technical and non-technical stakeholders

What We’re Looking For:

• 5+ years of experience in AI/ML model development
• Strong foundation in mathematics, probability, and statistics
• Proficiency in Python and exposure to Azure Machine Learning / Databricks
• Experience with supervised & unsupervised learning techniques
• Domain exposure to Energy / Oil & Gas value chain (preferred)
• Strong problem-solving, stakeholder management, and communication skills

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1 Year

CTC: ₹12 LPA

About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.

About the Role

We are looking for a highly motivated Software/Hardware Engineer from premier institutes (IIT/NIT) with strong fundamentals and a passion for building scalable and efficient systems. This role offers an opportunity to work on cutting-edge technology and solve real-world problems.

Key Responsibilities

Design, develop, and optimize software/hardware solutions

Work on system architecture, debugging, and performance improvements

Collaborate with cross-functional teams (product, design, operations)

Participate in code reviews, testing, and deployment processes

Contribute to innovation and continuous improvement initiatives

Requirements

B.Tech/M.Tech from IITs/NITs (Computer Science, Electronics, Electrical, or related fields)

1 year of experience (internships/project experience considered)

Strong programming skills (C/C++/Python/Java) or hardware fundamentals (embedded systems, VLSI, circuit design)

Good understanding of data structures, algorithms, and system design

Problem-solving mindset with strong analytical skills

Preferred Skills

Experience with embedded systems, IoT, or product development

Knowledge of cloud platforms or system-level programming

Good in Computer vision, Flutter, JavaScript, AI/ML

🔹 Role: Python Engineer – Python & MLOps

📍 Location: Bellandur, Bangalore

🕐 Work Timings: 01:30 PM – 10:30 PM

🏢 Work Mode: Monday (WFH), Tuesday–Friday (WFO)

📅 Experience: 8-12 Years (Ideal: 8-10 Years)

🔹 Role Overview

This role focuses on building and maintaining a production-grade AI/ML platform. You will work on scalable Python systems, MLOps pipelines, APIs, and CI/CD workflows in an enterprise environment.

🔹 Key Responsibilities

✔ Develop production-grade Python applications using OOP principles

✔ Build and enhance MLOps pipelines (training, validation, deployment)

✔ Design and optimize REST APIs with OpenAI/Swagger

✔ Implement async programming for high-performance systems

✔ Work on CI/CD pipelines (Azure Pipelines / GitHub Actions)

✔ Ensure clean, testable, and maintainable code (PyTest, TDD)

🔹 Required Skills

✔ Strong Python (OOP, modular design)

✔ MLOps & CI/CD pipeline experience

✔ REST API development

✔ Async programming (async/await, concurrency)

✔ Pandas / Polars & Scikit-learn

✔ JSON Schema–driven development

✔ Testing using PyTest

🔹 Nice to Have

➕ Azure ML SDK

➕ Pydantic

➕ Azure Cosmos DB

➕ Experience with large enterprise platforms

This role will report to the Chief Technology Officer

You Will Be Responsible For

* Driving decision-making on enterprise architecture and component-level software design to our software platforms' timely build and delivery.

* Leading a team in building a high-performing and scalable SaaS product.

* Conducting code reviews to maintain code quality and follow best practices

* DevOps practice development on promoting automation, including asset creation, enterprise strategy definition, and training teams

* Developing and building microservices leveraging cloud services

* Working on application security aspects

* Driving innovation within the engineering team, translating product roadmaps into clear development priorities, architectures, and timely release plans to drive business growth.

* Creating a culture of innovation that enables the continued growth of individuals and the company

* Working closely with Product and Business teams to build winning solutions

* Led talent management, including hiring, developing, and retaining a world-class team

Ideal Profile

* You possess a Degree in Engineering or a related field and have at least 20+ years of experience as a Software Engineer, with a 10+ years of experience leading teams and at least 4 Years of experience in building a SaaS / Fintech platform.

* Proficiency in MERN / Java / Full Stack.

* Led a team in optimizing the performance and scalability of a product

* You have extensive experience with DevOps environment and CI/CD practices and can train teams.

* You're a hands-on leader, visionary, and problem solver with a passion for excellence.

* You can work in fast-paced environments and communicate asynchronously with geographically distributed teams.

What's on Offer?

* Exciting opportunity to drive the Engineering efforts of a reputed organisation

* Work alongside & learn from best in class talent

* Competitive compensation + ESOPs

About the Role

We are looking for a passionate AI/ML Software Engineer to join our product team and help build intelligent, scalable, and production-ready machine learning solutions. You will work closely with product managers, designers, and backend engineers to integrate AI capabilities into core product features and drive data-driven innovation.

Key Responsibilities

• Design, develop, and deploy machine learning models into production environments
• Build and maintain scalable ML pipelines for data processing, training, and inference
• Collaborate with cross-functional teams to identify AI-driven product opportunities
• Translate business requirements into ML solutions and technical implementations
• Optimize model performance, accuracy, and latency for real-time applications
• Integrate AI/ML models with APIs and backend systems
• Monitor model performance and implement continuous improvement strategies
• Ensure best practices in data handling, model versioning, and reproducibility
• Stay updated with the latest advancements in AI/ML and apply them to product innovation

Required Skills & Qualifications

• Bachelor’s engineering degree in Computer Science, AI, Data Science, or related field
• Strong programming skills in Python (experience with Java/Go is a plus)
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Solid understanding of machine learning algorithms and statistical concepts
• Experience in building and deploying ML models in production
• Familiarity with REST APIs, microservices architecture, and cloud platforms (AWS/GCP/Azure)
• Experience with data processing tools (Pandas, NumPy, Spark, etc.)
• Knowledge of version control systems like Git 

Introduction

About Us:

Mercari is a Japan-based C2C marketplace company founded in 2013 with the mission to “Create value in a global marketplace where anyone can buy & sell.” From being the first tech unicorn from Japan before its IPO in 2018 we have come a long way towards becoming a global player and continuously and diligently work towards our transformation journey with a strong focus on our mission.

Since its inception, Mercari Group has worked to grow its services, investing in both our people and technology. Over time Mercari has expanded from being the top player in the C2C marketplace in Japan to new geographies like the U.S. We have also successfully launched new businesses such as Merpay, which is a mobile payment service platform with a vision to create a society where anyone can realize their dreams through a new ecosystem centered not only on payment service but also on credit. Today, Mercari Group is made up of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management.

For our services to be utilized by people worldwide; however, there is still a mountain of work ahead of us. This endeavor naturally requires the capability of the best talent and minds, and that is exactly the reason for us to launch the India Center of Excellence. With your help, we will continue to take on the world stage and strive to grow into a successful global tech company.

Our Culture:

To achieve our mission at Mercari, our organization and each of our employees share the same values and perspectives. Our individual guidelines for action are defined by our four values: Go Bold, All for One, Be a Pro and Move Fast. Our organization is also shaped by our four foundations: Sustainability, Diversity & Inclusion, Trust & Openness, and Well-being for Performance. Regardless of how big Mercari gets, the culture will remain essential to achieving our mission and something we want to preserve throughout our organization. We invite you to read the Mercari Culture Doc which summarizes the behaviors and mindset shared by Mercari and its employees. We continue to build an environment where all of our members of diverse backgrounds are accepted and recognized, and where they can thrive while holding dear to Mercari’s culture.

Work Responsibilities

• Machine learning engineers working in the Recommendation domain develop the functions and services of the marketplace app Mercari through the development and maintenance of machine learning systems like Recommender systems while leveraging necessary infrastructure and companywide platform tools. 
• Mercari is actively applying advanced machine learning technology to provide a more convenient, safer, and more enjoyable marketplace. Machine learning engineers use the cloud and Kubernetes to operate and improve machine learning systems.

Bold Challenges

• We are looking for people who are interested in our services, mission, and values, and want to work where engineers can go bold, use the latest technology, make autonomous decisions, and take on challenges at a rapid pace.
• Develop and optimize machine learning algorithms and models to enhance recommendation system to improve discovery experience of users
• Collaborate with cross-functional teams and product stakeholders to gather requirements, design solutions, and implement features that improve user engagement
• Conduct data analysis and experimentation with large-scale data sets to identify patterns, trends, and insights that drive the refinement of recommendation algorithms
• Utilize machine learning frameworks and libraries to deploy scalable and efficient recommendation solutions.
• Monitor system performance and conduct A/B testing to evaluate the effectiveness of features.
• Continuously research and stay updated on advancements in AI/machine learning techniques and recommend innovative approaches to enhance recommendation capabilities.

Minimum Requirements:

• Over 5-9 years of professional experience in end-to-end development of large-scale ML systems in production
• Strong experience demonstrating development and delivery of end-to-end machine learning solutions starting from experimentation to deploying models, including backend engineering and MLOps, in large scale production systems.
• Experience using common machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, NumPy, pandas)
• Deep understanding of machine learning and software engineering fundamentals
• Basic knowledge and skills related to monitoring system, logging, and common operations in production environment
• Communication skills to carry out projects in collaboration with multiple teams and stakeholders

Preferred skills:

• Experience developing Recommender systems utilizing large-scale data sets
• Basic knowledge of enterprise search systems and related stacks (e.g. ELK)
• Functional development and bug fixing skills necessary to improve system performance and reliability
• Experience with technology such as Docker and Kubernetes
• Experience with cloud platforms (AWS, GCP, Microsoft Azure, etc.)
• Microservice development and operation experience with Docker and Kubernetes
• Utilizing deep learning models/LLMs in production
• Experience in publications at top-tier peer-reviewed conferences or journals

Employment Status

Full-time

Office

Bangalore

Hybrid workstyle

• We believe in high performance and professionalism. We work from office for 2 days/week and work from home 3 days/week
• To build a strong & highly-engaged organization in India, we highly encourage everyone to work from our Bangalore office, especially during the initial office setup phase
• We will continue to review and update the policy to address future organizational needs

Work Hours

• Full flextime (no core time)

*Flexible to choose working hours other than team common meetings

Media

Owned Media

• Mercari Engineering Portal
• AI at Mercari portal
• Mercan - Introduces the people that make Mercari
• Mercari US Blog

Related Articles

• Development Platforms and Platformers: On Rising to the Global Standard Ken Wakasa, Mercari CTO | mercan
• “I'm Not a Talented Engineer” Insists the Member-Turned-Manager Revamping Our Internal CS Tool | mercan
• Personalize to globalize:How Mercari is reshaping their app, their company, and the world | mercan
• The Providers of the Safe and Secure Mercari Experience: The TnS Team, Introduced by Its Members! | mercan

Job Title: AI & Product Engineering Intern

Company: Optimo Capital (Nipun Projects and Finance Pvt. Ltd.) Location: Bengaluru, Karnataka (On-site / Hybrid) Duration: 4–6 months | Immediate / Rolling start Stipend: Based on profile

About Optimo Capital

Optimo Capital is an RBI-registered NBFC and India's first phygital Loan Against Property lender. We serve MSME business owners across 5 states, offering loans of ₹10L–₹2Cr with 4-day disbursal. Our tech team is actively building AI systems that redefine how lending operations work — from smart underwriting to autonomous calling agents to document intelligence and real-time property valuation.

What You'll Work On

You will be embedded in an early-stage fintech team working hands-on to make AI systems actually work in the real world — not in theory, not in demos, but in production. This means getting deep into existing projects — an autonomous AI calling system, an intelligent document extraction pipeline, and agentic AI frameworks — running experiments, figuring out what works and what doesn't, and iterating fast until it does.

Expect a lot of trial and error. Expect to think from first principles. Expect to question assumptions and find creative solutions to problems that don't have a textbook answer. The job is as much about curiosity and persistence as it is about technical skill.

Beyond the engineering, you will also be expected to think like a product person — understanding the business impact of what you build, owning parts of the product, and connecting the dots between what the AI does and why it matters to the business.

What We're Looking For

• Person with fundamental thinking in problem solving Currently pursuing or recently completed a degree in Computer Science, Mathematics, Statistics, or Engineering
• Solid programming fundamentals — Python, NodeJS etc and ability to learn new language if required
• Has shipped something: Internship, a project, a GitHub repo, a hackathon submission, or a research prototype that demonstrates end-to-end thinking
• Understands software systems beyond just writing code — APIs, data flows, system design at a basic level
• Can articulate the product reason behind technical decisions — not just "how" but "why"
• Comfortable working in ambiguity and taking ownership of open-ended problems

What Makes a Great Fit

We're looking for someone who reads about AI systems on weekends not because they have to, but because they're genuinely curious. You should be the kind of person who, when given a problem, immediately starts thinking about the product experience and the architecture simultaneously — and can hold both in your head at once. If you've built an LLM-powered tool, integrated a voice API, parsed messy documents, or simply gone deep on understanding how modern AI systems work under the hood — we'd love to talk.

Job Title : Azure Data Scientist (AI/ML)

Experience : 5 to 10 Years

Location : Bengaluru

Work Mode : Hybrid (4 Days WFO, Tue to Fri – Non-Negotiable)

Notice Period : Immediate Joiner

💡 Role Overview :

We are looking for a highly skilled Azure Data Scientist with strong expertise in AI/ML, Python, and cloud-based data platforms. The role involves building scalable ML solutions, working on GenAI & RAG use cases, and delivering business impact through data-driven insights.

🔥 Mandatory Skills :

Python, Azure Machine Learning, Databricks, AI/ML model development (5+ yrs), Statistics & Probability, EDA & Data Modeling, Machine Learning algorithms, GenAI/RAG experience

✅ Key Responsibilities :

• Design, develop, and deploy AI/ML models to solve complex business problems
• Perform Exploratory Data Analysis (EDA) for data cleaning, discovery, and insights
• Build and optimize ML pipelines using Azure Machine Learning & Databricks
• Work on GenAI applications, RAG implementations, and advanced analytics solutions
• Collaborate with data engineers, business stakeholders, and domain experts
• Translate complex data into actionable business insights
• Manage model lifecycle (development, validation, deployment, monitoring)
• Communicate model outputs and insights to technical & non-technical stakeholders
• Drive innovation and contribute to AI/ML best practices and strategy

🧠 Required Skills (Must Have) :

• Strong experience in Python (ML/AI development)
• Hands-on with Azure Machine Learning & Databricks
• Deep understanding of Mathematics, Probability, and Statistics
• Expertise in Machine Learning & Data Science methodologies
• Experience in EDA, data visualization, and model development
• Exposure to GenAI, RAG, and ML application development
• Minimum 5+ years of experience in AI/ML model development
• Strong problem-solving and analytical skills

➕ Good to Have :

• Experience with MLOps practices
• Domain knowledge in Energy / Oil & Gas value chain
• Experience in data visualization tools
• Team collaboration or mentoring experience

🤝 What We’re Looking For :

• Strong communication & stakeholder management skills
• Ability to work in a cross-functional, global team environment
• Self-driven, adaptable, and innovation-focused mindset

📝 Interview Process :

1. Geektrust Assessment (Assemble)
2. Technical Interview
3. Fitment Round
4. Client Round

Generative AI System Design

• Architect and implement end-to-end LLM-powered applications
• Build scalable RAG pipelines (chunking, embeddings, hybrid search, reranking)
• Design and implement agent-based workflows (tool calling, multi-step reasoning, orchestration)
• Integrate LLM APIs such as OpenAI and Anthropic, along with open-source models
• Implement structured output validation, grounding strategies, and hallucination mitigation
• Optimize inference cost, latency, and token efficiency
• Design evaluation pipelines for performance, accuracy, and safety

2️⃣ Backend & Microservices Engineering

• Design scalable backend systems using Python
• Build REST and async APIs using FastAPI / Django
• Architect and implement microservices with clear service boundaries
• Implement service-to-service communication (REST, gRPC, event-driven messaging)
• Work with message brokers (Kafka / RabbitMQ)
• Optimize database performance (PostgreSQL, MongoDB)
• Implement caching strategies (Redis)
• Build observability: logging, monitoring, distributed tracing

3️⃣ Cloud-Native Architecture & DevOps

• Design and deploy containerized services using Docker
• Orchestrate services using Kubernetes
• Implement CI/CD pipelines
• Ensure system scalability, resilience, and fault tolerance
• Apply distributed systems principles:
• Circuit breakers
• API gateway patterns
• Load balancing
• Horizontal scaling
• Saga patterns
• Zero-downtime deployments

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

Key Responsibilities

·      Design, develop, and deploy machine learning models for real-world business problems

·      Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

·      Implement and manage MLOps pipelines for scalable and reproducible workflows

·      Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

·      Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

·      Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

·      Optimize model performance and ensure production stability

·      Stay updated with the latest advancements in AI/ML and GenAI ecosystems

Required Skills & Qualifications

·      4+ years of experience in Data Science / Machine Learning

·      Strong programming skills in Python

·      Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

·      Solid understanding of MLOps practices and tools

·      Experience with MLflow or similar model lifecycle tools 

·      Practical experience in Generative AI (GenAI), including working with LLMs

·      Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

·      Strong understanding of data structures, algorithms, and statistics

·      Experience with cloud platforms (AWS/GCP/Azure) is a plus

Good to Have

·      Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

·      Exposure to Docker, Kubernetes, and CI/CD pipelines

·      Knowledge of data engineering workflows 

• 10+ years of software development experience
• 3+ years in a technical leadership role
• Strong expertise in Python and SQL
• Experience building scalable APIs and backend systems
• Solid understanding of database design and performance tuning
• Experience with Azure cloud services (AWS familiarity preferred)
• Working knowledge of ML/AI integration in enterprise systems
• Experience in client-facing or consulting environments preferred
• Experience with Databricks or modern data platforms
• Exposure to ETL tools such as Talend
• Experience with BI tools (e.g., Power BI)
• Exposure to regulated domains such as Pharma, Healthcare

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

🧭 Tech Lead (Backend / Fullstack | 7–10 Years)

Location: Bangalore (On-Site, Hybrid)

Company Type: Public-Listed Product Company

We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Lead execution of mission-critical systems while staying hands-on — bridging architecture and delivery.

🧩 What You’ll Do

• Own end-to-end delivery of complex engineering initiatives (0→1, 1→N)
• Design systems across backend + frontend (if fullstack)
• Translate ambiguous problems into structured technical solutions
• Drive engineering best practices, code quality, and velocity
• Mentor engineers and elevate team performance
• Collaborate with stakeholders on roadmap and execution strategy

🧠 What We’re Looking For

• Strong experience in backend systems + optional frontend frameworks
• Proven ability to lead projects and deliver at scale
• Solid understanding of system design and architecture patterns
• Ability to balance speed vs quality vs scalability trade-offs
• Strong communication and leadership without authority
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Experience leading platform builds or major system rewrites
• Exposure to AI systems, LLM integrations, or intelligent workflows
• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Background: We Commonly See (But Not Limited To)

• Our team often includes engineers from top-tier institutions and strong research or product company or DeepTech or AI Product backgrounds, including:
• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

🚨 We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Own and evolve the technical backbone of an AI-first enterprise platform.

You will define architecture across LLM-powered systems, distributed services, and data platforms — and lead critical transformations from legacy → AI-native systems.

🧩 What You’ll Do

• Architect large-scale distributed systems powering AI-driven workflows
• Lead 0→1 and 1→N platform builds (LLM integrations, agentic systems, orchestration layers)
• Redesign legacy systems into scalable, modular, AI-native architectures
• Drive system design excellence across teams (APIs, infra, observability, reliability)
• Make high-stakes decisions on trade-offs (latency, cost, scalability, model performance)
• Mentor senior engineers and influence engineering culture/org standards
• Partner with product, data, and leadership on long-term technical strategy

🧠 What We’re Looking For

• Proven track record building high-scale backend or platform systems
• Deep expertise in distributed systems, microservices, cloud (AWS/GCP/Azure)
• Strong exposure to data systems/infra / Data / real-time architectures
• Experience or strong interest in LLMs, GenAI, or AI system design
• Exceptional system design, abstraction, and problem-solving ability
• High ownership mindset — you think in terms of systems, not tickets
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset
• Solve hard system problems (latency, scale, reliability)
• Drive cross-team technical decisions and standards
• Mentor senior engineers and influence org-wide architecture 
• Design large-scale distributed systems and backend platforms
• Mentorship & Technical Leadership 
• Expertise in system design, scalability, and performance optimization

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Job Details

- Job Title: Director of Engineering

- Industry: SAAS

- Function – Information Technology

- Experience Required: 9-14 years

- Working Days: 6 days

- Employment Type: Full Time

- Job Location: Bangalore

- CTC Range: Best in Industry

Preferred Skills: TypeScript, AWS, NodeJS, mongodb, React.js, WebGL, Three.js, AI/ML, Docker,nKubernetes

Criteria

Candidate must be having 9+ years of engineering experience, with 3u20134 years in technical leadership

Hands-on expertise with React/Next.js, Node.js/Python, and AWS.

Ability to design scalable architectures for high-performance systems.

Should have AI/ML deployment experience

Strong 3D graphics/WebGL/Three.js knowledge.

Candidates should be from SAAS/Software/IT Services based startups or scaleup companies only

Job Description

The Role:

Company is hiring a hands-on Director of Engineering who codes, architects systems, and builds teams. You’ll set the technical foundation, drive engineering excellence, and own the architecture of our AI, 3D, and XR platform.

This is not a pure management role - expect to spend 50–60% of your time writing code, solving deep technical problems, and owning mission-critical systems. As we scale, this role transitions into CTO, taking full ownership of technical vision and long-term strategy. 

What You’ll Own:

1. Technical Leadership & Architecture

● Architect company’s full-stack platform across frontend, backend, infrastructure, and AI.

● Scale core systems: VersaAI engine, rendering pipeline, AR deployment, analytics.

● Make decisions on stack, scalability patterns, architecture, and technical debt.

● Own design for high-performance 3D asset processing, real-time rendering, and ML deployment.

● Lead architectural discussions, design reviews, and set engineering standards.

2. Hands-On Development

● Write production-grade code across frontend, backend, APIs, and cloud infra.

● Build critical features and core system components independently.

● Debug complex systems and optimize performance end-to-end.

● Implement and optimize AI/ML pipelines for 3D generation, CV, and recognition.

● Build scalable backend services for large-scale asset processing and real-time pipelines.

● Develop WebGL/Three.js rendering and AR workflows.

3. Team Building & Engineering Management

● Hire and grow a team of 5–8 engineers initially (scaling to 15–20).

● Establish engineering culture, values, and best practices.

● Build career frameworks, performance systems, and growth plans.

● Conduct 1:1s, mentor engineers, and drive continuous improvement.

● Set up processes for agile execution, deployments, and incident response.

4. Product & Cross-Functional Collaboration

● Work with the founder and product team on roadmap, feasibility, and prioritization.

● Translate product requirements into technical execution plans.

● Collaborate with design for UX quality and technical alignment.

● Support sales and customer success with integrations and technical discussions.

● Contribute technical inputs to product strategy and customer-facing initiatives.

5. Engineering Operations & Infrastructure

● Own CI/CD, testing frameworks, deployments, and automation.

● Create monitoring, logging, and alerting setups for reliability.

● Manage AWS infrastructure with a focus on cost and performance.

● Build internal tools, documentation, and developer workflows.

● Ensure enterprise-grade security, compliance, and reliability.

Tech Stack:

1. Frontend

React.js, Next.js, TypeScript, WebGL, Three.js

2. Backend

Node.js, Python, Express/FastAPI, REST, GraphQL

3. AI/ML

PyTorch, TensorFlow, CV models, Stable Diffusion, LLMs, ML pipelines

4. 3D & Graphics

Three.js, WebGL, Babylon.js, glTF, USDZ, rendering optimization

5. Databases

PostgreSQL, MongoDB, Redis, vector databases

6. Cloud & Infra

AWS (EC2, S3, Lambda, SageMaker), Docker, Kubernetes CI/CD: GitHub Actions

Monitoring: Datadog, Sentry

What We’re Looking For:

1. Must-Haves

● 9+ years of engineering experience, with 3–4 years in technical leadership.

● Deep full-stack experience with strong system design fundamentals.

● Proven success building products from 0→1 in fast-paced environments.

● Hands-on expertise with React/Next.js, Node.js/Python, and AWS.

● Ability to design scalable architectures for high-performance systems.

● Strong people leadership with experience hiring and mentoring teams.

● Ready to code, review, design, and lead from the front.

● Startup mindset: fast execution, problem-solving, ownership.

2. Highly Desirable

● AI/ML deployment experience (CV, generative AI, 3D reconstruction).

● Strong 3D graphics/WebGL/Three.js knowledge.

● Experience with real-time systems, rendering optimizations, or large-scale pipelines.

● Background in B2B SaaS, XR, gaming, or immersive tech.

● Experience scaling engineering teams from 5 → 20+.

● Open-source contributions or technical content creation.

● Experience working closely with founders or executive leadership.

Why Company:

● Hard, meaningful engineering problems at the intersection of AI, 3D, XR, and web tech.

● Build from day zero – architecture, team, and culture.

● Path to CTO as the company scales.

● High autonomy to drive technical decisions.

● Direct founder collaboration on product vision.

● High ownership, high-growth environment.

● Backed by global leaders: Microsoft, Google, NVIDIA, AWS.

Location & Work Culture:

● Location: HSR Layout, Bengaluru

● Schedule: 6 days a week, (5 days-in-office, Saturdays WFH)

● Culture: High-intensity, high-integrity, engineering-first

● Team: Young, ambitious, technically strong

We are looking for a highly skilled AI Platform Engineer to build and scale agentic AI capabilities across our product suite. You’ll work on multi‑agent systems, orchestration platforms, RAG pipelines, and real‑time AI services used in enterprise workflows.

🔹 Key Responsibilities

• Build and maintain AI platform services enabling agentic workflows
• Develop domain-specific agents (proposal generation, compliance, data analysis)
• Implement multi-agent orchestration using LangGraph and related frameworks
• Build APIs, SDKs, and integration layers for product teams
• Design and optimize RAG, GraphRAG, and knowledge ingestion pipelines
• Enhance orchestration platforms, WebSocket communication, and error recovery
• Optimize performance, latency (<3s), cost, and reliability of AI systems
• Collaborate closely with ML engineers and data scientists on models, prompts, and A/B testing

🔹 Required Skills & Experience

• 5+ years of software engineering experience (1–2+ years in AI/ML systems)
• Strong Python (FastAPI, async, LangChain/LangGraph)
• Experience with LLM APIs (OpenAI, Claude, Llama, Phi‑3)
• Hands-on RAG, embeddings, vector databases, and hybrid search
• React + TypeScript experience (WebSockets, hooks, real-time UI)
• Knowledge of multi-agent systems, prompt engineering, and orchestration patterns
• Solid backend fundamentals: REST APIs, databases, auth, testing, Git

🔹 Nice to Have

• MLOps exposure (prompt versioning, monitoring, A/B testing)
• Experience with semantic caching and context management
• Docker and cloud deployment basics

About CK-12 Foundation

CK-12’s mission is to provide free access to open-source content and technology tools that empower both students and teachers to enhance learning across different styles, resources, competence levels, and circumstances.

To achieve this ambitious vision, CK-12 challenges the traditional education model by leveraging technology to revolutionize learning for students, teachers, and parents.

CK-12 operates as a non-profit organization so it can experiment with bold ideas and focus on doing the right thing for education. The organization is backed by Vinod Khosla, a renowned technology venture capitalist.

At CK-12, you’ll work in a dynamic, entrepreneurial, and innovative environment where passionate individuals collaborate to disrupt traditional education through technology.

Technology is at the heart of scaling education, and CK-12 builds solutions on a cloud-based (AWS) and AI-first platform delivering rich and interactive learning experiences.

If you are a great technologist who enjoys challenging the status quo and building innovative products, this could be the place for you.

Together, we aim to transform education globally.

Product Offerings

Flexi 2.0 – AI-Powered Student Tutor

https://www.flexi.org/

AI-Powered Teacher Assistant

https://www.ck12.org/pages/teacher-assistant/

Core Responsibilities

• Translate high-level directions and open-ended product ideas into deliverable ML projects and drive their completion.

• Architect and implement highly scalable ML solutions for systems such as multimodal information retrieval, conversational chatbots, recommender systems, and ranking systems.

• Own end-to-end product delivery from research and experimentation to production deployment.

• Work closely with cross-functional teams including Product, Engineering, DevOps, QA, and Content teams.

• Manage ML workflows involving data gathering, working with annotators, and collaborating with ML researchers.

• Extract and analyze large volumes of data to generate insights about student and teacher behavior based on platform usage.

• Design and build innovative ML-driven solutions that can improve learning experiences in the EdTech space.

• Apply statistical hypothesis testing and experimentation to evaluate and improve models.

• Continuously innovate and challenge the traditional approach to education through ML solutions.

Requirements

• Bachelor’s degree or higher in Computer Science or a related quantitative discipline, or equivalent practical experience.

• 4+ years of hands-on development experience with strong programming skills, preferably in Python.

• Expertise in deep learning approaches for NLP including transformer-based models, predictive modeling, search and recommendation systems, and autoregressive models.

• 2+ years of experience in NLP applications such as information retrieval, chatbots, summarization, or generative models.

• Proven experience building scalable ML applications on cloud infrastructure such as AWS, GCP, or Azure.

• Strong understanding of trade-offs between model architecture, deployment costs, and model accuracy.

• Ability to manage multiple tasks and collaborate effectively with geographically distributed teams.

• Up-to-date knowledge of advancements in NLP and computer vision and the ability to apply them in the education domain.

Technical Skills

• Python, PyTorch, TorchServe

• Pandas

• SQL and NoSQL databases such as MySQL, MongoDB, Redis, and Redshift

• Cloud infrastructure (AWS / GCP / Azure)

• Vector databases and search technologies such as Elasticsearch

• Linux

Nice to Have

• Familiarity with Reinforcement Learning

• Experience with Deep Knowledge Tracing

About Us:

REConnect Energy’s GRIDConnect platform helps integrate and manage energy generation and consumption for 1000s of renewable energy assets and grid operators. We are currently serving customers across India, Bhutan and the Middle East with expansion planned in US and European markets.

We are headquartered in Central Bangalore with a team of 150+ and growing. You will join the Bangalore based Engineering team as a senior member and work at the intersection of Energy, Weather & Climate Sciences and AI. 

Responsibilities:

● Engineering - Take complete ownership of engineering stacks including Data Engineering and MLOps. Define and maintain software systems architecture for high availability 24x7 systems.

● Leadership - Lead a team of engineers and analysts managing engineering development as well as round the clock service delivery. Provide mentorship and technical guidance to team members and contribute towards their professional growth. Manage weekly and monthly reviews with team members and senior management.

● Product Development - Contribute towards new product development through engineering solutions to product requirements. Interact with cross-functional teams to bring forward a technology perspective.

● Operations - Manage delivery of critical services to power utilities with expectations of zero downtime. Take ownership for uninterrupted product uptime. 

Requirements:

● 4-5 years of experience building highly available systems

● 2-3 years experience leading a team of engineers and analysts

● Bachelors or Master’s degree in Computer Science, Software Engineering, Electrical Engineering or equivalent

● Proficient in python programming skills and expertise with data engineering and machine learning deployment

● Experience in databases including MySQL and NoSQL

● Experience in developing and maintaining critical and high availability systems will be given strong preference

● Experience in software design using design principles and architectural modeling.

● Experience working with AWS cloud platform.

● Strong analytical and data driven approach to problem solving 

Description

JOB DESCRIPTION – SENIOR ANALYST – DATA SCIENTIST 

Key Responsibilities ·       

Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions·       

Advanced skills with statistical/programming in Python and data querying languages (e.g., SQL, Hadoop/Hive, Scala)·       

Solid understanding of time-series forecasting techniques·       

Good hands-on skills in both feature engineering and hyperparameter optimization·       

Able to write clean and tested code that can be maintained by other software engineers·       

Able to clearly summarize and communicate data analysis assumptions and results·       

Able to craft effective data pipelines to transform your analyses from offline to production systems·       

Self-motivated and a proactive problem solver who can work independently and in teams·       

Connects both externally and internally to understand industry trends, technology advances and outstanding processes or solutions·       

Is collaborative and engages (strategic & tactical. Able to influence without authority, handle complex issues and implement positive change·       

Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science·       

Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment ·       

Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential·       

Lead discussions at peer review and use interpersonal skills to positively influence decision making·       

Provide subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices·       

Facilitate cross-geography sharing of new ideas, learnings, and best-practices 

What We Are Looking For 

Required Qualifications ·       

Master's degree in a quantitative field such as Data Science, Statistics, Applied Mathematics or Bachelor's degree in engineering, computer science, or related field. ·       

4 – 6 years of total work experience as data scientist or analytical role, with at least 2-3 years of experience in time series forecasting·       

A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project ·       

Strong experience in Time Series Forecasting and Demand Planning ·       

Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) ·       

Good hands-on skills in both feature engineering and hyperparameter optimization ·       

Experience producing high-quality code, tests, documentation·       

Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies·       

Proficiency in statistical concepts and ML algorithms·       

Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team·       

Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results·       

Self-motivated and a proactive problem solver who can work independently and in teams·       

Outstanding verbal and written communication skills with the ability to effectively advocate technical solutions to engineering and business teams 

Desired Qualifications ·      

Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred ·       

Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred ·       

Experience in creating CI/CD pipelines for deployment using Jenkins. ·       

Experience implementing MLOPs framework along with understanding of data security·       

Implementation on ML models·       

Exposure to visualization packages and Azure tech stack.  

Must have skills

Python - 2 years

Data Science - 4 years

SQL - 2 years

Machine Learning - 2 years

Nice to have skills

Data Analysis - 4 years

Time Series Forecasting - 2 years

Demand Planning - 2 years

Hadoop - 2 years

Statistical concepts - 2 years

Supply chain functions - 2 years

Hi ,

Title                            : Senior AI/ML Engineer

Experience                 : 5 – 10+ Yrs

Location                     : Bengaluru

Work Type                : Hybrid – 2 days Work from office

Type of hire               : PwD & Non-PwD Inclusive Hiring

Employment Type     : Full Time

Notice Period             : Immediate Joiner

Workdays                   : Mon - Fri

Role Overview

We are seeking an exceptional AI Engineer who can design and build production-grade AI systems that combine advanced machine learning, Generative AI, and scalable software engineering.

This role goes beyond traditional data science and focuses on building end-to-end AI platforms, autonomous AI agents, intelligent decision systems, and enterprise AI applications.

You will work on real-world enterprise problems across industries, developing AI systems that automate reasoning, prediction, and decision-making at scale.

What You Will Build

Examples of systems you may work on:

• AI Copilots for enterprise workflows

• Autonomous AI agents for automation

• Decision intelligence platforms

• Retrieval-Augmented Generation (RAG) systems

• Predictive ML systems for forecasting and anomaly detection

• AI-powered knowledge assistants

• Intelligent automation platforms

Key Responsibilities

1. Advanced Machine Learning & Predictive Systems

Design and implement ML models including:

• Time series forecasting

• Predictive modeling

• Anomaly detection

• Recommendation systems

• NLP / text intelligence

• Deep learning models

Develop models using:

• PyTorch

• TensorFlow

• Scikit-learn

• XGBoost / LightGBM

2. Generative AI & LLM Systems

Build enterprise-grade GenAI applications including:

• AI copilots

• conversational agents

• document intelligence systems

• enterprise knowledge assistants

Develop LLM systems using:

• OpenAI / Claude / Gemini / Llama

• prompt engineering techniques

• embeddings and semantic search

• RAG architectures

3. Agentic AI Systems

Design autonomous AI systems capable of reasoning and executing tasks.

Build multi-agent architectures using:

• LangGraph

• CrewAI

• AutoGen

• Semantic Kernel

Integrate agents with:

• APIs

• enterprise data systems

• internal workflows

4. AI Platform Engineering

Develop scalable AI services and applications using:

• Python

• FastAPI / Flask

• asynchronous processing

• distributed compute frameworks

Build production-grade APIs and AI services.

5. Enterprise AI Deployment & MLOps

Deploy AI models into scalable production environments.

Work with:

• Docker

• Kubernetes

• CI/CD pipelines

• MLflow / experiment tracking

• model monitoring and drift detection

Deploy AI solutions on:

• Azure

• AWS

• GCP

6. Data Integration & AI Systems

Work with enterprise data sources including:

• relational databases

• data warehouses (Snowflake, Redshift, BigQuery)

• data lakes (S3 / Azure Data Lake)

• vector databases (Pinecone, Weaviate, FAISS)

Required Skills:

Programming

Expert-level proficiency in:

• Python

• software engineering best practices

• data structures and algorithms

Experience building production-ready systems.

Machine Learning

Strong expertise in:

• supervised learning

• unsupervised learning

• deep learning

• time-series modelling

• model evaluation and optimization

Generative AI

Experience working with:

• LLM APIs

• prompt engineering

• RAG pipelines

• embeddings and vector search

AI Architecture

Ability to design:

• scalable AI systems

• distributed ML systems

• intelligent automation platforms

Preferred Experience

• Building enterprise AI products

• Developing AI copilots or agents

• Designing decision intelligence platforms

• Experience with large-scale data systems

Ideal Candidate Profile

The ideal candidate is:

• A strong ML engineer AND software engineer

• Comfortable building AI systems end-to-end

• Experienced in deploying models to production

• Passionate about next-generation AI architectures

We value builders who ship real systems, not just research prototypes.

Education

Bachelor’s / Master’s in:

Computer Science

Artificial Intelligence

Machine Learning

Data Science

or related field.

Why Join Ampera

At Ampera, we are building AI-native enterprise platforms that transform how organizations use data and intelligence.

Engineers at Ampera work on:

• real-world enterprise AI systems

• cutting-edge GenAI and agentic architectures

• global enterprise clients across industries

• high-impact AI platforms that scale.

What Makes This Role Unique

You will help build the next generation of enterprise AI systems — where AI moves beyond prediction and becomes an autonomous decision-making layer for organizations.

About Ampera:

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

.

Job Responsibilities

• Help develop an analytics platform that integrates insights from diverse data sources.
• Build, deploy, and test machine learning and classification models
• Train and retrain systems when necessary
• Design experiments, train and track performance of machine learning and AI models that meet specific business requirements
• ML and data labelling: Identify ways to gather and build training data with automated data labelling techniques and the creation of highly accurate training datasets.
• Automatic extraction of causal knowledge from diverse information sources such as databases, news, social media, videos and images etc.
• Develop customized machine learning solutions including data querying and knowledge extraction.
• Develop and implement approaches for extracting patterns and correlations from both internal and external data sources using time series machine learning models.
• Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors.
• Distil insights from complex data, communicating findings to technical and non-technical audiences.
• Develop, improve, or expand in-house computational pipelines, algorithms, models, and services used in crop product development.
• Constantly document and communicate results of research on data mining, analysis, and modelling approaches.
• 5+ years of experience working with NLP and ML technologies.
• Proven experience as a Machine Learning Engineer or similar role.
• Experience with NLP/ML frameworks and libraries       
• Proficient with Python scripting language
• Background in machine learning frameworks like TensorFlow, PyTorch, Scikit Learn, etc.
• Demonstrated experience developing and executing machine learning, deep learning, data mining and classification models. Conversant with the latest in NLP and NLU models including transformer architectures and in creating explainable AI
• Ability to communicate the advantages and disadvantages of choosing specific models to various stakeholders
• Proficient with relational databases and SQL. Ability to write efficient queries and optimize the storage and retrieval of data within the database. Experience with creating and working on APIs, Serverless architectures and Containers.
• Creative, innovative, and strategic thinking; willingness to be bold and take risks on new ideas.

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Mandatory Skills: AI : Artificial Intelligence .

Experience: 8-10 Years .

Title: Quantitative Developer

Location : Mumbai

Candidates preferred with Master's

Who We Are

At Dolat Capital, we are a collective of traders, puzzle solvers, and tech enthusiasts passionate about decoding the intricacies of financial markets. From navigating volatile trading conditions with precision to continuously refining cutting-edge technologies and quantitative strategies, our work thrives at the intersection of finance and engineering.

We operate a robust, ultra-low latency infrastructure built for market-making and active trading across Equities, Futures, and Options—with some of the highest fill rates in the industry. If you're excited by technology, trading, and critical thinking, this is the place to evolve your skills into world class capabilities.

What You Will Do

This role offers a unique opportunity to work across both quantitative development and high frequency trading. You'll engineer trading systems, design and implement algorithmic strategies, and directly participate in live trading execution and strategy enhancement.

1. Quantitative Strategy & Trading Execution

• Design, implement, and optimize quantitative strategies for trading derivatives, index options, and ETFs
• Trade across options, equities, and futures, using proprietary HFT platforms
• Monitor and manage PnL performance, targeting Sharpe ratios of 6+
• Stay proactive in identifying market opportunities and inefficiencies in real-time HFT environments
• Analyze market behavior, particularly in APAC indices, to adjust models and positions dynamically

2. Trading Systems Development

• Build and enhance low-latency, high-throughput trading systems
• Develop tools to simulate trading strategies and access historical market data
• Design performance-optimized data structures and algorithms for fast execution
• Implement real-time risk management and performance tracking systems

3. Algorithmic and Quantitative Analysis

• Collaborate with researchers and traders to integrate strategies into live environments
• Use statistical methods and data-driven analysis to validate and refine models
• Work with large-scale HFT tick data using Python / C++

4. AI/ML Integration

• Develop and train AI/ML models for market prediction, signal detection, and strategy enhancement
• Analyze large datasets to detect patterns and alpha signals

5. System & Network Optimization

• Optimize distributed and concurrent systems for high-transaction throughput
• Enhance platform performance through network and systems programming
• Utilize deep knowledge of TCP/UDP and network protocols

6. Collaboration & Mentorship

• Collaborate cross-functionally with traders, engineers, and data scientists
• Represent Dolat in campus recruitment and industry events as a technical mentor

What We Are Looking For:

• Strong foundation in data structures, algorithms, and object-oriented programming (C++).
• Experience with AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience in systems programming within a Linux environment.
• Proficient and Hands on programming using python/ C++
• Familiarity with distributed computing and high-concurrency systems.
• Knowledge of network programming, including TCP/UDP protocols.
• Strong analytical and problem-solving skills.

A passion for technology-driven solutions in the financial markets.

Key Responsibilities

· Advanced ML & Deep Learning: Design, develop, and deploy end-to-end Machine Learning models for Content Recommendation Engines, Churn Prediction, and Customer Lifetime Value (CLV).

· Generative AI Implementation: Prototype and integrate GenAI solutions (using LLMs like Gemini/GPT) for automated Metadata Tagging, Script Summarization, or AI-driven Chatbots for viewer engagement.

· Develop and maintain high-scale video processing pipelines using Python, OpenCV, and FFmpeg to automate scene detection, ad-break identification, and visual feature extraction for content enrichment

· Cloud Orchestration: Utilize GCP (Vertex AI, BigQuery, Dataflow) to build scalable data pipelines and manage the full ML lifecycle (MLOps).

· Business Intelligence & Storytelling: Create high-impact, automated dashboards in to track KPIs for data-driven decision making

· Cross-functional Collaboration: Work closely with Product, Design, Engineering, Content, and Marketing teams to translate "viewership data" into "strategic growth."

Preferred Qualifications

· Experience in Media/OTT: Prior experience working with large scale data from broadcast channels, videos, streaming platforms or digital ad-tech.

· Education: Master’s/Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, or Data Science).

· Product Mindset: Ability to not just build a model, but to understand the business implications of the solution.

· Communication: Exceptional ability to explain "Neural Network outputs" to a "Creative Content Producer" in simple terms.

JOB DETAILS:

* Job Title: Principal Data Scientist

* Industry: Healthcare

* Salary: Best in Industry

* Experience: 6-10 years

* Location: Bengaluru

Preferred Skills: Generative AI, NLP & ASR, Transformer Models, Cloud Deployment, MLOps

Criteria:

1. Candidate must have 7+ years of experience in ML, Generative AI, NLP, ASR, and LLMs (preferably healthcare).
2. Candidate must have strong Python skills with hands-on experience in PyTorch/TensorFlow and transformer model fine-tuning.
3. Candidate must have experience deploying scalable AI solutions on AWS/Azure/GCP with MLOps, Docker, and Kubernetes.
4. Candidate must have hands-on experience with LangChain, OpenAI APIs, vector databases, and RAG architectures.
5. Candidate must have experience integrating AI with EHR/EMR systems, ensuring HIPAA/HL7/FHIR compliance, and leading AI initiatives.

Job Description

Principal Data Scientist

(Healthcare AI | ASR | LLM | NLP | Cloud | Agentic AI)

Job Details

• Designation: Principal Data Scientist (Healthcare AI, ASR, LLM, NLP, Cloud, Agentic AI)
• Location: Hebbal Ring Road, Bengaluru
• Work Mode: Work from Office
• Shift: Day Shift
• Reporting To: SVP
• Compensation: Best in the industry (for suitable candidates)

Educational Qualifications

• Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• Technical certifications in AI/ML, NLP, or Cloud Computing are an added advantage

Experience Required

• 7+ years of experience solving real-world problems using:
• Natural Language Processing (NLP)
• Automatic Speech Recognition (ASR)
• Large Language Models (LLMs)
• Machine Learning (ML)
• Preferably within the healthcare domain
• Experience in Agentic AI, cloud deployments, and fine-tuning transformer-based models is highly desirable

Role Overview

This position is part of company, a healthcare division of Focus Group specializing in medical coding and scribing.

We are building a suite of AI-powered, state-of-the-art web and mobile solutions designed to:

• Reduce administrative burden in EMR data entry
• Improve provider satisfaction and productivity
• Enhance quality of care and patient outcomes

Our solutions combine cutting-edge AI technologies with live scribing services to streamline clinical workflows and strengthen clinical decision-making.

The Principal Data Scientist will lead the design, development, and deployment of cognitive AI solutions, including advanced speech and text analytics for healthcare applications. The role demands deep expertise in generative AI, classical ML, deep learning, cloud deployments, and agentic AI frameworks.

Key Responsibilities

AI Strategy & Solution Development

• Define and develop AI-driven solutions for speech recognition, text processing, and conversational AI
• Research and implement transformer-based models (Whisper, LLaMA, GPT, T5, BERT, etc.) for speech-to-text, medical summarization, and clinical documentation
• Develop and integrate Agentic AI frameworks enabling multi-agent collaboration
• Design scalable, reusable, and production-ready AI frameworks for speech and text analytics

Model Development & Optimization

• Fine-tune, train, and optimize large-scale NLP and ASR models
• Develop and optimize ML algorithms for speech, text, and structured healthcare data
• Conduct rigorous testing and validation to ensure high clinical accuracy and performance
• Continuously evaluate and enhance model efficiency and reliability

Cloud & MLOps Implementation

• Architect and deploy AI models on AWS, Azure, or GCP
• Deploy and manage models using containerization, Kubernetes, and serverless architectures
• Design and implement robust MLOps strategies for lifecycle management

Integration & Compliance

• Ensure compliance with healthcare standards such as HIPAA, HL7, and FHIR
• Integrate AI systems with EHR/EMR platforms
• Implement ethical AI practices, regulatory compliance, and bias mitigation techniques

Collaboration & Leadership

• Work closely with business analysts, healthcare professionals, software engineers, and ML engineers
• Implement LangChain, OpenAI APIs, vector databases (Pinecone, FAISS, Weaviate), and RAG architectures
• Mentor and lead junior data scientists and engineers
• Contribute to AI research, publications, patents, and long-term AI strategy

Required Skills & Competencies

• Expertise in Machine Learning, Deep Learning, and Generative AI
• Strong Python programming skills
• Hands-on experience with PyTorch and TensorFlow
• Experience fine-tuning transformer-based LLMs (GPT, BERT, T5, LLaMA, etc.)
• Familiarity with ASR models (Whisper, Canary, wav2vec, DeepSpeech)
• Experience with text embeddings and vector databases
• Proficiency in cloud platforms (AWS, Azure, GCP)
• Experience with LangChain, OpenAI APIs, and RAG architectures
• Knowledge of agentic AI frameworks and reinforcement learning
• Familiarity with Docker, Kubernetes, and MLOps best practices
• Understanding of FHIR, HL7, HIPAA, and healthcare system integrations
• Strong communication, collaboration, and mentoring skills

Hi,

Greetings from Ampera!

we are looking for a Data Scientist with strong Python & Forecasting experience.

Title                               : Data Scientist – Python & Forecasting

Experience                   : 4 to 7 Yrs

Location                       : Chennai/Bengaluru

Type of hire                  : PWD and Non PWD

Employment Type     : Full Time

Notice Period             : Immediate Joiner

Working hours           : 09:00 a.m. to 06:00 p.m.

Workdays                   : Mon - Fri

Job Description:

We are looking for an experienced Data Scientist with strong expertise in Python programming and forecasting techniques. The ideal candidate should have hands-on experience building predictive and time-series forecasting models, working with large datasets, and deploying scalable solutions in production environments.

Key Responsibilities

• Develop and implement forecasting models (time-series and machine learning based).
• Perform exploratory data analysis (EDA), feature engineering, and model validation.
• Build, test, and optimize predictive models for business use cases such as demand forecasting, revenue prediction, trend analysis, etc.
• Design, train, validate, and optimize machine learning models for real-world business use cases.
• Apply appropriate ML algorithms based on business problems and data characteristics
• Write clean, modular, and production-ready Python code.
• Work extensively with Python Packages & libraries for data processing and modelling.
• Collaborate with Data Engineers and stakeholders to deploy models into production.
• Monitor model performance and improve accuracy through continuous tuning.
• Document methodologies, assumptions, and results clearly for business teams.

Technical Skills Required:

Programming

• Strong proficiency in Python
• Experience with Pandas, NumPy, Scikit-learn

Forecasting & Modelling

• Hands-on experience in Time Series Forecasting (ARIMA, SARIMA, Prophet, etc.)
• Experience with ML-based forecasting models (XGBoost, LightGBM, Random Forest, etc.)
• Understanding of seasonality, trend decomposition, and statistical modeling

Data & Deployment

• Experience handling structured and large datasets
• SQL proficiency
• Exposure to model deployment (API-based deployment preferred)
• Knowledge of MLOps concepts is an added advantage

Tools (Preferred)

• TensorFlow / PyTorch (optional)
• Airflow / MLflow
• Cloud platforms (AWS / Azure / GCP)

Educational Qualification

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field.

Key Competencies

• Strong analytical and problem-solving skills
• Ability to communicate insights to technical and non-technical stakeholders
• Experience working in agile or fast-paced environments

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

ROLE - TECH LEAD/ARCHITECT with AI Expertise

Experience: 10–15 Years

Location: Bangalore (Onsite)

Company Type: Product-based | AI B2B SaaS

About ProductNova

ProductNova is a fast-growing product development organization that partners with

ambitious companies to build, modernize, and scale high-impact digital products. Our teams

of product leaders, engineers, AI specialists, and growth experts work at the intersection of

strategy, technology, and execution to help organizations create differentiated product

portfolios and accelerate business outcomes.

Founded in early 2023, ProductNova has successfully designed, built, and launched 20+

large-scale, AI-powered products and platforms across industries. We specialize in solving

complex business problems through thoughtful product design, robust engineering, and

responsible use of AI.

Product Development

We design and build user-centric, scalable, AI-native B2B SaaS products that are deeply

aligned with business goals and long-term value creation.

Our end-to-end product development approach covers the full lifecycle:

1. Product discovery and problem definition

2. User research and product strategy

3. Experience design and rapid prototyping

4. AI-enabled engineering, testing, and platform architecture

5. Product launch, adoption, and continuous improvement

From early concepts to market-ready solutions, we focus on building products that are

resilient, scalable, and ready for real-world adoption. Post-launch, we work closely with

customers to iterate based on user feedback and expand products across new use cases,

customer segments, and markets.

Growth & Scale

For early-stage companies and startups, we act as product partners—shaping ideas into

viable products, identifying target customers, achieving product-market fit, and supporting

go-to-market execution, iteration, and scale.

For established organizations, we help unlock the next phase of growth by identifying

opportunities to modernize and scale existing products, enter new geographies, and build

entirely new product lines. Our teams enable innovation through AI, platform re-

architecture, and portfolio expansion to support sustained business growth.

Role Overview

We are looking for a Tech Lead / Architect to drive the end-to-end technical design and

development of AI-powered B2B SaaS products. This role requires a strong hands-on

technologist who can work closely with ML Engineers and Full Stack Development teams,

own the product architecture, and ensure scalability, security, and compliance across the

platform.

Key Responsibilities

• Lead the end-to-end architecture and development of AI-driven B2B SaaS products

• Collaborate closely with ML Engineers, Data Scientists, and Full Stack Developers to

integrate AI/ML models into production systems

• Define and own the overall product technology stack, including backend, frontend,

data, and cloud infrastructure

• Design scalable, resilient, and high-performance architectures for multi-tenant SaaS

platforms

• Drive cloud-native deployments (Azure) using modern DevOps and CI/CD practices

• Ensure data privacy, security, compliance, and governance (SOC2, GDPR, ISO, etc.)

across the product

• Take ownership of application security, access controls, and compliance

requirements

• Actively contribute hands-on through coding, code reviews, complex feature development and architectural POCs

• Mentor and guide engineering teams, setting best practices for coding, testing, and

system design

• Work closely with Product Management and Leadership to translate business

requirements into technical solutions

Qualifications:

• 10–15 years of overall experience in software engineering and product

development

• Strong experience building B2B SaaS products at scale

• Proven expertise in system architecture, design patterns, and distributed systems

• Hands-on experience with cloud platforms (Azure, AWS/GCP)

• Solid background in backend technologies (Python/ .NET / Node.js / Java) and

modern frontend frameworks like (React, JS, etc.)

• Experience working with AI/ML teams in deploying and tuning ML models into production

environments

• Strong understanding of data security, privacy, and compliance frameworks

• Experience with microservices, APIs, containers, Kubernetes, and cloud-native

architectures

• Strong working knowledge of CI/CD pipelines, DevOps, and infrastructure as code

• Excellent communication and leadership skills with the ability to work cross-

functionally

• Experience in AI-first or data-intensive SaaS platforms

• Exposure to MLOps frameworks and model lifecycle management

• Experience with multi-tenant SaaS security models

• Prior experience in product-based companies or startups

Why Join Us

• Build cutting-edge AI-powered B2B SaaS products

• Own architecture and technology decisions end-to-end

• Work with highly skilled ML and Full Stack teams

• Be part of a fast-growing, innovation-driven product organization

If you are a results-driven Technical Lead with a passion for developing innovative products that drives business growth, we invite you to join our dynamic team at ProductNova.

Hi,

PFB the Job Description for Data Science with ML

Type of hire                  : PWD and Non PWD

Employment Type    : Full Time

Notice Period            : Immediate Joiner

Work Days                    : Mon - Fri

About Ampera:

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards

About the Role

We are looking for a skilled Data Scientist with strong Machine Learning experience to design, develop, and deploy data-driven solutions. The role involves working with large datasets, building predictive and ML models, and collaborating with cross-functional teams to translate business problems into analytical solutions.

Key Responsibilities

• Analyze large, structured and unstructured datasets to derive actionable insights.
• Design, build, validate, and deploy Machine Learning models for prediction, classification, recommendation, and optimization.
• Apply statistical analysis, feature engineering, and model evaluation techniques.
• Work closely with business stakeholders to understand requirements and convert them into data science solutions.
• Develop end-to-end ML pipelines including data preprocessing, model training, testing, and deployment.
• Monitor model performance and retrain models as required.
• Document assumptions, methodologies, and results clearly.
• Collaborate with data engineers and software teams to integrate models into production systems.
• Stay updated with the latest advancements in data science and machine learning.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in computer science, Data Science, Statistics, Mathematics, or related fields.
• 5+ years of hands-on experience in Data Science and Machine Learning.
• Strong proficiency in Python (NumPy, Pandas, Scikit-learn).
• Experience with ML algorithms:
• Regression, Classification, Clustering
• Decision Trees, Random Forest, Gradient Boosting
• SVM, KNN, Naïve Bayes
• Solid understanding of statistics, probability, and linear algebra.
• Experience with data visualization tools (Matplotlib, Seaborn, Power BI, Tableau – preferred).
• Experience working with SQL and relational databases.
• Knowledge of model evaluation metrics and optimization techniques.

Preferred / Good to Have

• Experience with Deep Learning frameworks (TensorFlow, PyTorch, Keras).
• Exposure to NLP, Computer Vision, or Time Series forecasting.
• Experience with big data technologies (Spark, Hadoop).
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Experience with MLOps, CI/CD pipelines, and model deployment.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder interaction skills.
• Ability to work independently and in cross-functional teams.
• Curiosity and willingness to learn new tools and techniques.

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

.

Required Skills & Qualifications

● Strong hands-on experience with LLM frameworks and models, including LangChain,

OpenAI (GPT-4), and LLaMA

● Proven experience in LLM orchestration, workflow management, and multi-agent

system design using frameworks such as LangGraph

● Strong problem-solving skills with the ability to propose end-to-end solutions and

contribute at an architectural/system design level

● Experience building scalable AI-backed backend services using FastAPI and

asynchronous programming patterns

● Solid experience with cloud infrastructure on AWS, including EC2, S3, and Load

Balancers

● Hands-on experience with Docker and containerization for deploying and managing

AI/ML applications

● Good understanding of Transformer-based architectures and how modern LLMs work

internally

● Strong skills in data processing and analysis using NumPy and Pandas

● Experience with data visualization tools such as Matplotlib and Seaborn for analysis

and insights

● Hands-on experience with Retrieval-Augmented Generation (RAG), including

document ingestion, embeddings, and vector search pipelines

● Experience in model optimization and training techniques, including fine-tuning,

LoRA, and QLoRA

Nice to Have / Preferred

● Experience designing and operating production-grade AI systems

● Familiarity with cost optimization, observability, and performance tuning for

LLM-based applications

● Exposure to multi-cloud or large-scale AI platforms

Job Title: AI/ML Engineer – Voice (2–3 Years)

Location: Bengaluru (On-site)

Employment Type: Full-time

About Impacto Digifin Technologies

Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.

We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.

Role Overview

We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.

This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.

You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.

This role is collaborative, cross-functional, and hands-on.

Key Responsibilities

Voice AI Engineering

• Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
• Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
• Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
• Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
• Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
• Implement voice understanding modules, speech intent extraction, and context tracking.

Machine Learning & Deep Learning

• Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
• Train and fine-tune neural networks for text, speech, and multimodal tasks.
• Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
• Perform feature engineering, model evaluation, retraining, and continuous learning cycles.

NLP, LLMs & GenAI

• Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
• Work with LLM architectures for text + voice workflows
• Build GenAI-based workflows and integrate models into production systems.
• Implement RAG pipelines and agent-based systems for complex automation.

Fintech & Banking AI

• Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
• Understand fintech data structures and constraints while designing AI models.

Engineering, Deployment & Collaboration

• Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
• Build robust APIs and services for voice and ML-based functionalities.
• Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
• Document systems and contribute to internal knowledge bases and R&D.

Security & Compliance

• Follow fundamental best practices for AI security, access control, and safe data handling.
• Awareness of financial compliance standards (plus, not mandatory).
• Follow internal guidelines on PII, audio data, and model privacy.

Primary Skills (Must-Have)

Core AI

• Machine Learning fundamentals
• Deep Learning architectures
• NLP pipelines and transformers
• LLM usage and integration
• GenAI development
• Voice AI (STT, TTS, VAD, real-time pipelines)
• Audio processing fundamentals
• Model building, tuning, and retraining
• RAG systems
• AI Agents (orchestration, multi-step reasoning)

Voice Engineering

• End-to-end voice application development
• Voice calling & telephony integration (framework-agnostic)
• Realtime STT ↔ LLM ↔ TTS interactive flows
• Voice chat system development
• Voice-to-AI model integration for automation

Fintech/Banking Awareness

• High-level understanding of fintech and banking AI use cases
• Data patterns in core banking analytics (advantageous)

Programming & Engineering

• Python (strong competency)
• Cloud deployment understanding (AWS/Azure/GCP)
• API development
• Data processing & pipeline creation

Secondary Skills (Good to Have)

• MLOps & CI/CD for ML systems
• Vector databases
• Prompt engineering
• Model monitoring & evaluation frameworks
• Microservices experience
• Basic UI integration understanding for voice/chat
• Research reading & benchmarking ability

Qualifications

• 2–3 years of practical experience in AI/ML/DL engineering.
• Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
• Proven hands-on experience building ML/DL/voice pipelines.
• Experience in fintech or data-intensive domains preferred.

Soft Skills

• Clear communication and requirement understanding
• Curiosity and research mindset
• Self-driven problem solving
• Ability to collaborate cross-functionally
• Strong ownership and delivery discipline
• Ability to explain complex AI concepts simply

Job Title : Senior Software Engineer (Full Stack — AI/ML & Data Applications)

Experience : 5 to 10 Years

Location : Bengaluru, India

Employment Type : Full-Time | Onsite

Role Overview :

We are seeking a Senior Full Stack Software Engineer with strong technical leadership and hands-on expertise in AI/ML, data-centric applications, and scalable full-stack architectures.

In this role, you will design and implement complex applications integrating ML/AI models, lead full-cycle development, and mentor engineering teams.

Mandatory Skills :

Full Stack Development (React/Angular/Vue + Node.js/Python/Java), Data Engineering (Spark/Kafka/ETL), ML/AI Model Integration (TensorFlow/PyTorch/scikit-learn), Cloud & DevOps (AWS/GCP/Azure, Docker, Kubernetes, CI/CD), SQL/NoSQL Databases (PostgreSQL/MongoDB).

Key Responsibilities :

• Architect, design, and develop scalable full-stack applications for data and AI-driven products.
• Build and optimize data ingestion, processing, and pipeline frameworks for large datasets.
• Deploy, integrate, and scale ML/AI models in production environments.
• Drive system design, architecture discussions, and API/interface standards.
• Ensure engineering best practices across code quality, testing, performance, and security.
• Mentor and guide junior developers through reviews and technical decision-making.
• Collaborate cross-functionally with product, design, and data teams to align solutions with business needs.
• Monitor, diagnose, and optimize performance issues across the application stack.
• Maintain comprehensive technical documentation for scalability and knowledge-sharing.

Required Skills & Experience :

• Education : B.E./B.Tech/M.E./M.Tech in Computer Science, Data Science, or equivalent fields.
• Experience : 5+ years in software development with at least 2+ years in a senior or lead role.
• Full Stack Proficiency :
• Front-end : React / Angular / Vue.js
• Back-end : Node.js / Python / Java
• Data Engineering : Experience with data frameworks such as Apache Spark, Kafka, and ETL pipeline development.
• AI/ML Expertise : Practical exposure to TensorFlow, PyTorch, or scikit-learn and deploying ML models at scale.
• Databases : Strong knowledge of SQL & NoSQL systems (PostgreSQL, MongoDB) and warehousing tools (Snowflake, BigQuery).
• Cloud & DevOps : Working knowledge of AWS, GCP, or Azure; containerization & orchestration (Docker, Kubernetes); CI/CD; MLflow/SageMaker is a plus.
• Visualization : Familiarity with modern data visualization tools (D3.js, Tableau, Power BI).

Soft Skills :

• Excellent communication and cross-functional collaboration skills.
• Strong analytical mindset with structured problem-solving ability.
• Self-driven with ownership mentality and adaptability in fast-paced environments.

Preferred Qualifications (Bonus) :

• Experience deploying distributed, large-scale ML or data-driven platforms.
• Understanding of data governance, privacy, and security compliance.
• Exposure to domain-driven data/AI use cases in fintech, healthcare, retail, or e-commerce.
• Experience working in Agile environments (Scrum/Kanban).
• Active open-source contributions or a strong GitHub technical portfolio.

Skills: Gen AI, Machine learning Models, AWS/ Azure, redshift, Python, Apachi, Airflow, Devops, minimum 4-5years experience as Architect, should be from Data Engineering background.

• 8+ years of experience in data engineering, data science, or architecture roles.

• Experience designing enterprise-grade AI platforms.

• Certification in major cloud platforms (AWS/Azure/GCP).

• Experience with governance tooling (Collibra, Alation) and lineage systems

• Strong hands-on background in data engineering, analytics, or data science.

• Expertise in building data platforms using:

o Cloud: AWS (Glue, S3, Redshift), Azure (Data Factory, Synapse), GCP (BigQuery,

Dataflow).

o Compute: Spark, Databricks, Flink.

o Data modelling: dimensional, relational, NoSQL, graph.

• Proficiency with Python, SQL, and data pipeline orchestration tools.

• Understanding of ML frameworks and tools: TensorFlow, PyTorch, Scikit-learn, MLflow, etc.

• Experience implementing MLOps, model deployment, monitoring, logging, and versioning.

Experience: 3+ years

Responsibilities:

• Build, train and fine tune ML models
• Develop features to improve model accuracy and outcomes.
• Deploy models into production using Docker, kubernetes and cloud services.
• Proficiency in Python, MLops, expertise in data processing and large scale data set.
• Hands on experience in Cloud AI/ML services.
• Exposure in RAG Architecture

Senior Machine Learning Engineer

About the Role

We are looking for a Senior Machine Learning Engineer who can take business problems, design appropriate machine learning solutions, and make them work reliably in production environments.

This role is ideal for someone who not only understands machine learning models, but also knows when and how ML should be applied, what trade-offs to make, and how to take ownership from problem understanding to production deployment.

Beyond technical skills, we need someone who can lead a team of ML Engineers, design end-to-end ML solutions, and clearly communicate decisions and outcomes to both engineering teams and business stakeholders. If you enjoy solving real problems, making pragmatic decisions, and owning outcomes from idea to deployment, this role is for you.

What You’ll Be Doing

Building and Deploying ML Models

• Design, build, evaluate, deploy, and monitor machine learning models for real production use cases.
• Take ownership of how a problem is approached, including deciding whether ML is the right solution and what type of ML approach fits the problem.
• Ensure scalability, reliability, and efficiency of ML pipelines across cloud and on-prem environments.
• Work with data engineers to design and validate data pipelines that feed ML systems.
• Optimize solutions for accuracy, performance, cost, and maintainability, not just model metrics.

Leading and Architecting ML Solutions

• Lead a team of ML Engineers, providing technical direction, mentorship, and review of ML approaches.
• Architect ML solutions that integrate seamlessly with business applications and existing systems.
• Ensure models and solutions are explainable, auditable, and aligned with business goals.
• Drive best practices in MLOps, including CI/CD, model monitoring, retraining strategies, and operational readiness.
• Set clear standards for how ML problems are framed, solved, and delivered within the team.

Collaborating and Communicating

• Work closely with business stakeholders to understand problem statements, constraints, and success criteria.
• Translate business problems into clear ML objectives, inputs, and expected outputs.
• Collaborate with software engineers, data engineers, platform engineers, and product managers to integrate ML solutions into production systems.
• Present ML decisions, trade-offs, and outcomes to non-technical stakeholders in a simple and understandable way.

What We’re Looking For

Machine Learning Expertise

• Strong understanding of supervised and unsupervised learning, deep learning, NLP techniques, and large language models (LLMs).
• Experience choosing appropriate modeling approaches based on the problem, available data, and business constraints.
• Experience training, fine-tuning, and deploying ML and LLM models for real-world use cases.
• Proficiency in common ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.

Production and Cloud Deployment

• Hands-on experience deploying and running ML systems in production environments on AWS, GCP, or Azure.
• Good understanding of MLOps practices, including CI/CD for ML models, monitoring, and retraining workflows.
• Experience with Docker, Kubernetes, or serverless architectures is a plus.
• Ability to think beyond deployment and consider operational reliability and long-term maintenance.

Data Handling

• Strong programming skills in Python.
• Proficiency in SQL and working with large-scale datasets.
• Ability to reason about data quality, data limitations, and how they impact ML outcomes.
• Familiarity with distributed computing frameworks like Spark or Dask is a plus.

Leadership and Communication

• Ability to lead and mentor ML Engineers and work effectively across teams.
• Strong communication skills to explain ML concepts, decisions, and limitations to business teams.
• Comfortable taking ownership and making decisions in ambiguous problem spaces.
• Passion for staying updated with advancements in ML and AI, with a practical mindset toward adoption.

Experience Needed

• 6+ years of experience in machine learning engineering or related roles.
• Proven experience designing, selecting, and deploying ML solutions used in production.
• Experience managing ML systems after deployment, including monitoring and iteration.
• Proven track record of working in cross-functional teams and leading ML initiatives.

Job Description: 

Exp Range - [6y to 10y]

Qualifications:

• Minimum Bachelors Degree in Engineering or Computer Applications or AI/Data science
• Experience working in product companies/Startups for developing, validating, productionizing AI model in the recent projects in last 3 years.
• Prior experience in Python, Numpy, Scikit, Pandas, ETL/SQL, BI tools in previous roles preferred

Require Skills: 

• Must Have – Direct hands-on experience working in Python for scripting automation analysis and Orchestration
• Must Have – Experience working with ML Libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy etc.
• Must Have – Experience working with models such as Random forest, Kmeans clustering, BERT…
• Should Have – Exposure to querying warehouses and APIs
• Should Have – Experience with writing moderate to complex SQL queries
• Should Have – Experience analyzing and presenting data with BI tools or Excel
• Must Have – Very strong communication skills to work with technical and non technical stakeholders in a global environment

Roles and Responsibilities:

• Work with Business stakeholders, Business Analysts, Data Analysts to understand various data flows and usage.
• Analyse and present insights about the data and processes to Business Stakeholders
• Validate and test appropriate AI/ML models based on the prioritization and insights developed while working with the Business Stakeholders
• Develop and deploy customized models on Production data sets to generate analytical insights and predictions
• Participate in cross functional team meetings and provide estimates of work as well as progress in assigned tasks.
• Highlight risks and challenges to the relevant stakeholders so that work is delivered in a timely manner.
• Share knowledge and best practices with broader teams to make everyone aware and more productive.

Job Overview:

As a Technical Lead, you will be responsible for leading the design, development, and deployment of AI-powered Edtech solutions. You will mentor a team of engineers, collaborate with data scientists, and work closely with product managers to build scalable and efficient AI systems. The ideal candidate should have 8-10 years of experience in software development, machine learning, AI use case development and product creation along  with strong expertise in cloud-based architectures.

Key Responsibilities:

AI Tutor & Simulation Intelligence

• Architect the AI intelligence layer that drives contextual tutoring, retrieval-based reasoning, and fact-grounded explanations.
• Build RAG (retrieval-augmented generation) pipelines and integrate verified academic datasets from textbooks and internal course notes.
• Connect the AI Tutor with the Simulation Lab, enabling dynamic feedback — the system should read experiment results, interpret them, and explain why outcomes occur.
• Ensure AI responses remain transparent, syllabus-aligned, and pedagogically accurate.

Platform & System Architecture

• Lead the development of a modular, full-stack platform unifying courses, explainers, AI chat, and simulation windows in a single environment.
• Design microservice architectures with API bridges across content systems, AI inference, user data, and analytics.
• Drive performance, scalability, and platform stability — every millisecond and every click should feel seamless.

Reliability, Security & Analytics

• Establish system observability and monitoring pipelines (usage, engagement, AI accuracy).
• Build frameworks for ethical AI, ensuring transparency, privacy, and student safety.
• Set up real-time learning analytics to measure comprehension and identify concept gaps.

Leadership & Collaboration

• Mentor and elevate engineers across backend, ML, and front-end teams.
• Collaborate with the academic and product teams to translate physics pedagogy into engineering precision.
• Evaluate and integrate emerging tools — multi-modal AI, agent frameworks, explainable AI — into the product roadmap.

Qualifications & Skills:

• 8–10 years of experience in software engineering, ML systems, or scalable AI product builds.
• Proven success leading cross-functional AI/ML and full-stack teams through 0→1 and scale-up phases.
• Expertise in cloud architecture (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
• Experience designing microservices and API ecosystems for high-concurrency platforms.
• Strong knowledge of LLM fine-tuning, RAG pipelines, and vector databases (Pinecone, Weaviate, etc.).
• Demonstrated ability to work with educational data, content pipelines, and real-time systems.

Bonus Skills (Nice to Have):

• Experience with multi-modal AI models (text, image, audio, video).
• Knowledge of AI safety, ethical AI, and explain ability techniques.
• Prior work in AI-powered automation tools or AI-driven SaaS products.

Job Description – Senior Technical Business Analyst

Location: Trivandrum (Preferred) | Open to any location in India

Shift Timings - 8 hours window between the 7:30 PM IST - 4:30 AM IST

About the Role

We are seeking highly motivated and analytically strong Senior Technical Business Analysts who can work seamlessly with business and technology stakeholders to convert a one-line problem statement into a well-defined project or opportunity. This role is ideal for fresh graduates who have a strong foundation in data analytics, data engineering, data visualization, and data science, along with a strong drive to learn, collaborate, and grow in a dynamic, fast-paced environment.

As a Technical Business Analyst, you will be responsible for translating complex business challenges into actionable user stories, analytical models, and executable tasks in Jira. You will work across the entire data lifecycle—from understanding business context to delivering insights, solutions, and measurable outcomes.

Key Responsibilities

Business & Analytical Responsibilities

• Partner with business teams to understand one-line problem statements and translate them into detailed business requirements, opportunities, and project scope.
• Conduct exploratory data analysis (EDA) to uncover trends, patterns, and business insights.
• Create documentation including Business Requirement Documents (BRDs), user stories, process flows, and analytical models.
• Break down business needs into concise, actionable, and development-ready user stories in Jira.

Data & Technical Responsibilities

• Collaborate with data engineering teams to design, review, and validate data pipelines, data models, and ETL/ELT workflows.
• Build dashboards, reports, and data visualizations using leading BI tools to communicate insights effectively.
• Apply foundational data science concepts such as statistical analysis, predictive modeling, and machine learning fundamentals.
• Validate and ensure data quality, consistency, and accuracy across datasets and systems.

Collaboration & Execution

• Work closely with product, engineering, BI, and operations teams to support the end-to-end delivery of analytical solutions.
• Assist in development, testing, and rollout of data-driven solutions.
• Present findings, insights, and recommendations clearly and confidently to both technical and non-technical stakeholders.

Required Skillsets

Core Technical Skills

• 6+ years of Technical Business Analyst experience within an overall professional experience of 8+ years
• Data Analytics: SQL, descriptive analytics, business problem framing.
• Data Engineering (Foundational): Understanding of data warehousing, ETL/ELT processes, cloud data platforms (AWS/GCP/Azure preferred).
• Data Visualization: Experience with Power BI, Tableau, or equivalent tools.
• Data Science (Basic/Intermediate): Python/R, statistical methods, fundamentals of ML algorithms.

Soft Skills

• Strong analytical thinking and structured problem-solving capability.
• Ability to convert business problems into clear technical requirements.
• Excellent communication, documentation, and presentation skills.
• High curiosity, adaptability, and eagerness to learn new tools and techniques.

Educational Qualifications

• BE/B.Tech or equivalent in:
• Computer Science / IT
• Data Science

What We Look For

• Demonstrated passion for data and analytics through projects and certifications.
• Strong commitment to continuous learning and innovation.
• Ability to work both independently and in collaborative team environments.
• Passion for solving business problems using data-driven approaches.
• Proven ability (or aptitude) to convert a one-line business problem into a structured project or opportunity.

Why Join Us?

• Exposure to modern data platforms, analytics tools, and AI technologies.
• A culture that promotes innovation, ownership, and continuous learning.
• Supportive environment to build a strong career in data and analytics.

Skills: Data Analytics, Business Analysis, Sql

Must-Haves

Technical Business Analyst (6+ years), SQL, Data Visualization (Power BI, Tableau), Data Engineering (ETL/ELT, cloud platforms), Python/R

Strong Senior Data Scientist (AI/ML/GenAI) Profile

Mandatory (Experience 1) – Must have a minimum of 5+ years of experience in designing, developing, and deploying Machine Learning / Deep Learning (ML/DL) systems in production

Mandatory (Experience 2) – Must have strong hands-on experience in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.

Mandatory (Experience 3) – Must have 1+ years of experience in fine-tuning Large Language Models (LLMs) using techniques like LoRA/QLoRA, and building RAG (Retrieval-Augmented Generation) pipelines.

Mandatory (Experience 4) – Must have experience with MLOps and production-grade systems including Docker, Kubernetes, Spark, model registries, and CI/CD workflows

mandatory (Note): Budget for upto 5 yoe is 25Lacs, Upto 7 years is 35 lacs and upto 12 years is 45 lacs, Also client can pay max 30-40% based on candidature

We are looking for enthusiastic engineers passionate about building and maintaining solutioning platform components on cloud and Kubernetes infrastructure. The ideal candidate will go beyond traditional SRE responsibilities by collaborating with stakeholders, understanding the applications hosted on the platform, and designing automation solutions that enhance platform efficiency, reliability, and value.

[Technology and Sub-technology]

• ML Engineering / Modelling

• Python Programming

• GPU frameworks: TensorFlow, Keras, Pytorch etc.

• Cloud Based ML development and Deployment AWS or Azure

[Qualifications]

• Bachelor’s Degree in Computer Science, Computer Engineering or equivalent technical degree

• Proficient programming knowledge in Python or Java and ability to read and explain open source codebase.

• Good foundation of Operating Systems, Networking and Security Principles

• Exposure to DevOps tools, with experience integrating platform components into Sagemaker/ECR and AWS Cloud environments.

• 4-6 years of relevant experience working on AI/ML projects

[Primary Skills]:

• Excellent analytical & problem solving skills.

• Exposure to Machine Learning and GenAI technologies.

• Understanding and hands-on experience with AI/ML Modeling, Libraries, frameworks, and Tools (TensorFlow, Keras, Pytorch etc.)

• Strong knowledge of Python, SQL/NoSQL

• Cloud Based ML development and Deployment AWS or Azure

Review Criteria

• Strong Senior Data Scientist (AI/ML/GenAI) Profile
• 5+ years of experience in designing, developing, and deploying Machine Learning / Deep Learning (ML/DL) systems in production
• Must have strong hands-on experience in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• 1+ years of experience in fine-tuning Large Language Models (LLMs) using techniques like LoRA/QLoRA, and building RAG (Retrieval-Augmented Generation) pipelines.
• Must have experience with MLOps and production-grade systems including Docker, Kubernetes, Spark, model registries, and CI/CD workflows

Preferred

• Prior experience in open-source GenAI contributions, applied LLM/GenAI research, or large-scale production AI systems
• Preferred (Education) – B.S./M.S./Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.

Job Specific Criteria

• CV Attachment is mandatory
• Which is your preferred job location (Mumbai / Bengaluru / Hyderabad / Gurgaon)?
• Are you okay with 3 Days WFO?
• Virtual Interview requires video to be on, are you okay with it?

Role & Responsibilities

Company is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.

Responsibilities:

• Own the full ML lifecycle: model design, training, evaluation, deployment
• Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
• Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
• Build agentic workflows for reasoning, planning, and decision-making
• Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
• Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
• Collaborate with product and engineering teams to integrate AI models into business applications
• Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices

Ideal Candidate

• 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
• Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
• Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
• Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
• Strong software engineering background with experience in testing, version control, and APIs
• Proven ability to balance innovation with scalable deployment
• B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
• Bonus: Open-source contributions, GenAI research, or applied systems at scale

Job Title: Sensor Expert – MLFF (Multi-Lane Free Flow) Engagement Type: Consultant / External Associate Organization: Bosch - MPIN

Location: Bangalore, India

Purpose of the Role:

To provide technical expertise in sensing technologies for MLFF (Multi-Lane Free Flow) and ITMS (Intelligent Traffic Management System) solutions. The role focuses on camera systems, AI/ML based computer vision, and multi-sensor integration (camera, RFID, radar) to drive solution performance, optimization, and business success. Key

Responsibilities:

• Lead end-to-end sensor integration for MLFF and ITMS platforms.

• Manage camera systems, ANPR, and data packet processing.

• Apply AI/ML techniques for performance optimization in computer vision.

• Collaborate with System Integrators and internal teams on architecture and implementation.

• Support B2G proposals (smart city, mining, infrastructure projects) with domain expertise.

• Drive continuous improvement in deployed MLFF solutions. 

Key Competencies:

• Deep understanding of camera and sensor technologies, AI/ML for vision systems, and system integration.

• Experience in PoC development and solution optimization.

• Strong analytical, problem-solving, and collaboration skills.

• Familiarity with B2G environments and public infrastructure tenders preferred.

Qualification & Experience:

• Bachelor’s/Master’s in Electronics, Electrical, or Computer Science.

• 8–10 years of experience in camera technology, AI/ML, and sensor integration.

• Proven track record in system design, implementation, and field optimization.

AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.

Implementation and testing of advanced computer vision algorithms.

Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.

Detailed analysis of results. Documentation, version control, client support, upgrades.

Experience- 6 to 8 years

Location- Bangalore

Job Description-

- Extensive experience with machine learning utilizing the latest analytical models in Python. (i.e., experience in generating data-driven insights that play a key role in rapid decision-making and driving business outcomes.)

- Extensive experience using Tableau, table design, PowerApps, Power BI, Power Automate, and cloud environments, or equivalent experience designing/implementing data analysis pipelines and visualization.

- Extensive experience using AI agent platforms. (AI = data analysis: a required skill for data analysts.)

- A statistics major or equivalent understanding of statistical analysis results interpretation.

Job Title: AI Engineer

Location: Bengaluru 

Experience: 3 Years 

Working Days: 5 Days

About the Role

We’re reimagining how enterprises interact with documents and workflows—starting with BFSI and healthcare. Our AI-first platforms are transforming credit decisioning, document intelligence, and underwriting at scale. The focus is on Intelligent Document Processing (IDP), GenAI-powered analysis, and human-in-the-loop (HITL) automation to accelerate outcomes across lending, insurance, and compliance workflows.

As an AI Engineer, you’ll be part of a high-caliber engineering team building next-gen AI systems that:

• Power robust APIs and platforms used by underwriters, credit analysts, and financial institutions.
• Build and integrate GenAI agents.
• Enable “human-in-the-loop” workflows for high-assurance decisions in real-world conditions.

Key Responsibilities

• Build and optimize ML/DL models for document understanding, classification, and summarization.
• Apply LLMs and RAG techniques for validation, search, and question-answering tasks.
• Design and maintain data pipelines for structured and unstructured inputs (PDFs, OCR text, JSON, etc.).
• Package and deploy models as REST APIs or microservices in production environments.
• Collaborate with engineering teams to integrate models into existing products and workflows.
• Continuously monitor and retrain models to ensure reliability and performance.
• Stay updated on emerging AI frameworks, architectures, and open-source tools; propose improvements to internal systems.

Required Skills & Experience

• 2–5 years of hands-on experience in AI/ML model development, fine-tuning, and building ML solutions.
• Strong Python proficiency with libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of transformers, embeddings, and NLP pipelines.
• Experience working with LLMs (OpenAI, Claude, Gemini, etc.) and frameworks like LangChain.
• Exposure to OCR, document parsing, and unstructured text analytics.
• Familiarity with model serving, APIs, and microservice architectures (FastAPI, Flask).
• Working knowledge of Docker, cloud environments (AWS/GCP/Azure), and CI/CD pipelines.
• Strong grasp of data preprocessing, evaluation metrics, and model validation workflows.
• Excellent problem-solving ability, structured thinking, and clean, production-ready coding practices.

Full Stack Engineer

Position Description

Responsibilities

• Take design mockups provided by UX/UI designers and translate them into web pages or applications using HTML and CSS. Ensure that the design is faithfully replicated in the final product.

• Develop enabling frameworks and application E2E and enhance with data analytics and AI enablement

• Ensure effective Design, Development, Validation and Support activities in line with the Customer needs, architectural requirements, and ABB Standards.

• Support ABB business units through consulting engagements.

• Develop and implement machine learning models to solve specific business problems, such as predictive analytics, classification, and recommendation systems

• Perform exploratory data analysis, clean and preprocess data, and identify trends and patterns.

• Evaluate the performance of machine learning models and fine-tune them for optimal results.

• Create informative and visually appealing data visualizations to communicate findings and insights to non-technical stakeholders.

• Conduct statistical analysis, hypothesis testing, and A/B testing to support decision-making processes.

• Define the solution, Project plan, identifying and allocation of team members, project tracking; Work with data engineers to integrate, transform, and store data from various sources.

• Collaborate with cross-functional teams, including business analysts, data engineers, and domain experts, to understand business objectives and develop data science solutions.

• Prepare clear and concise reports and documentation to communicate results and methodologies.

• Stay updated with the latest data science and machine learning trends and techniques.

• Familiarity with ML Model Deployment as REST APIs.

Background

• Engineering graduate / Masters degree with rich exposure to Data science, from a reputed institution

• Create responsive web designs that adapt to different screen sizes and devices using media queries and responsive design techniques.

• Write and maintain JavaScript code to add interactivity and dynamic functionality to web pages. This may include user input handling, form validation, and basic animations.

• Familiarity with front-end JavaScript libraries and frameworks such as React, Angular, or Vue.js. Depending on the projects, you may be responsible for working within these frameworks

• Atleast 6+ years experience in AI ML concepts, Python (preferred), prefer knowledge in deep learning frameworks like PyTorch and TensorFlow

• Domain knowledge of Manufacturing/ process Industries, Physics and first principle based analysis

• Analytical thinking for translating data into meaningful insight and could be consumed by ML Model for Training and Prediction.

• Should be able to deploy Model using Cloud services like Azure Databricks or Azure ML Studio. Familiarity with technologies like Docker, Kubernetes and MLflow is good to have.

• Agile development of customer centric prototypes or ‘Proof of Concepts’ for focused digital solutions

• Good communication skills must be able to discuss the requirements effectively with the client teams, and with internal teams.

Hi Shanon, As discussed we have one open req for AI role. The right skill set I am looking for is experience with RAG pipelines, Performance monitoring of prompts and tuning. Multi model RAG and agentic AI soon but not night away. Needless to say Python and the NLP lib experience is a must. Database knowledge is also essential. The developer needs to be in Morgan Stanley offices 3 days per week. BLR location is preferred, if not Mumbai is also fine. The duration is long term since we are looking to expand the use cases Please let me know if you have any questions. 

Role: Data Scientist (Python + R Expertise)

Exp: 8 -12 Years

CTC: up to 30 LPA

Required Skills & Qualifications:

• 8–12 years of hands-on experience as a Data Scientist or in a similar analytical role.
• Strong expertise in Python and R for data analysis, modeling, and visualization.
• Proficiency in machine learning frameworks (scikit-learn, TensorFlow, PyTorch, caret, etc.).
• Strong understanding of statistical modeling, hypothesis testing, regression, and classification techniques.
• Experience with SQL and working with large-scale structured and unstructured data.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and deployment practices (Docker, MLflow).
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

• Experience with NLP, time series forecasting, or deep learning projects.
• Exposure to data visualization tools (Tableau, Power BI, or R Shiny).
• Experience working in product or data-driven organizations.
• Knowledge of MLOps and model lifecycle management is a plus.

If interested kindly share your updated resume on 82008 31681

Role: Sr. Data Scientist

Exp: 4 -8 Years

CTC: up to 28 LPA

Technical Skills:

o Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.

o Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.

o Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.

o Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.

o Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).

o Exposure to natural language processing (NLP) techniques is a plus.

Cloud & Infrastructure:

o Strong expertise in Azure cloud ecosystem,

o Experience working in UNIX/Linux environments and using command-line tools for automation and scripting.

If interested kindly share your updated resume at 82008 31681

Role: Sr. Data Scientist

Exp: 4-8 Years

CTC: up to 25 LPA

Technical Skills:

● Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.

● Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.

● Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.

● Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.

● Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).

● Exposure to natural language processing (NLP) techniques is a plus.

• Educational Qualifications:

• B.E./B.Tech/M.Tech/MCA in Computer Science, Electronics & Communication, Electrical Engineering, or a related field.
• A master’s degree in computer science, Artificial Intelligence, or a specialization in Deep Learning or Computer Vision is highly preferred

If interested share your resume on 82008 31681