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

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PFB the Job Description for Data Science with ML

Title                                  : Data Scientist - Machine Learning

Experience                   : 5+ 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.

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.

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Job Description: 

Exp Range - [5y to 10y]

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.
• Analyze 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.

Qualifications:

• Minimum bachelor's 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

This role is at Glance

What you will be doing

We are looking for a Data Scientist who can operate at the intersection of classical machine learning, large-scale recommendation systems, and modern agentic AI systems.

You will design, build, and deploy intelligent systems that power Glance’s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.

Your responsibilities will include:

Classical ML & Recommendation Systems

• Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
• Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
• Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
• Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
• Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.

Agentic Systems & Next-Gen AI

• Build and experiment with agentic AI systems that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention.
• Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models for semantic understanding, content classification, and user preference modeling.
• Design intelligent agents that can automate repetitive decision-making tasks—e.g., candidate generation tuning, feature selection, or context-aware content curation.
• Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.

Cross-functional impact

• Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance’s consumer experiences.
• Contribute to Glance’s ML/AI thought leadership—blogs, case studies, internal tech talks, and industry conferences.
• Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
• Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.

The experience we need

We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.

You should have experience with:

• Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
• Classical ML and deep learning techniques across NLP, sequence modeling, RL, clustering, and time series.
• Experience in deploying ML workflows/models in production system
• Big data processing (Spark, distributed data systems) and cloud computing.
• Designing end-to-end ML solutions—from prototype to production.
• Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).

We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.

Qualifications

• Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
• 4+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
• Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
• Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
• Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
• Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
• Comfortable working in cross-functional teams.
• Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
• Excellent communication skills with the ability to simplify complex technical concepts.

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

Role Overview:

We are looking for a PHP & Angular Developer to build and maintain scalable full-stack web applications. The role requires strong backend expertise in PHP, solid frontend development using Angular, and exposure or interest in AI/ML-powered features.

Key Responsibilities:

• Develop and maintain applications using PHP and Angular
• Build and consume RESTful APIs
• Create reusable Angular components using TypeScript
• Work with MySQL/PostgreSQL databases
• Collaborate with Product, QA, and AI/ML teams
• Integrate AI/ML APIs where applicable
• Ensure performance, security, and scalability
• Debug and resolve production issues

Required Skills:

• 5–7 years experience in PHP development
• Strong hands-on with Laravel / CodeIgniter
• Experience with Angular (v10+)
• HTML, CSS, JavaScript, TypeScript
• REST APIs, JSON
• MySQL / PostgreSQL
• Git, MVC architecture

Good to Have:

• Exposure to AI/ML concepts or API integrations
• Python-based ML services (basic)
• Cloud platforms (AWS / Azure / GCP)
• Docker, CI/CD
• Agile/Scrum experience
• Product/start-up background

Role Overview:

We are looking for a PHP & Angular Developer to build and maintain scalable full-stack web applications. The role requires strong backend expertise in PHP, solid frontend development using Angular, and exposure or interest in AI/ML-powered features.

Key Responsibilities:

• Develop and maintain applications using PHP and Angular
• Build and consume RESTful APIs
• Create reusable Angular components using TypeScript
• Work with MySQL/PostgreSQL databases
• Collaborate with Product, QA, and AI/ML teams
• Integrate AI/ML APIs where applicable
• Ensure performance, security, and scalability
• Debug and resolve production issues

Required Skills:

• 5–7 years experience in PHP development
• Strong hands-on with Laravel / CodeIgniter
• Experience with Angular (v10+)
• HTML, CSS, JavaScript, TypeScript
• REST APIs, JSON
• MySQL / PostgreSQL
• Git, MVC architecture

Good to Have:

• Exposure to AI/ML concepts or API integrations
• Python-based ML services (basic)
• Cloud platforms (AWS / Azure / GCP)
• Docker, CI/CD
• Agile/Scrum experience
• Product/start-up background

The Opportunity

Planview is looking for a passionate Sr Data Scientist to join our team tasked with developing innovative tools for connected work. You are an experienced expert in supporting enterprise

 applications using Data Analytics, Machine Learning, and Generative AI.

You will use this experience to lead other data scientists and data engineers. You will also effectively engage with product teams to specify, validate, prototype, scale, and deploy features with a consistent customer experience across the Planview product suite.

Responsibilities (What you'll do)

• Enable Data Science features within Planview applications by working in a fast-paced start-up mindset.
• Collaborate closely with product management to enable Data Science features that deliver significant value to customers, ensuring that these features are optimized for operational efficiency.
• Manage every stage of the AI/ML development lifecycle, from initial concept through deployment in a production environment.
• Provide leadership to other Data Scientists by exemplifying exceptional quality in work, nurturing a culture of continuous learning, and offering daily guidance in their research endeavors.
• Effectively communicate ideas drawn from complex data with clarity and insight.

Qualifications (What you'll bring)

• Master’s in operations research, Statistics, Computer Science, Data Science, or related field.
• 8+ years of experience as a data scientist, data engineer, or ML engineer.
• Demonstrable history for bringing Data Science features to Enterprise applications.
• Exceptional Python and SQL coding skills.
• Experience with Optimization, Machine Learning, Generative AI, NLP, Statistics, and Simulation.
• Experience with AWS Data and ML Technologies (Sagemaker, Glue, Athena, Redshift)

Preferred qualifications:

• Experience working with datasets in the domains of project management, software development, and resource planning.
• Experience with common libraries and frameworks in data science (Scikit Learn, TensorFlow, PyTorch).
• Experience with ML platform tools (AWS SageMaker).
• Skilled at working as part of a global, diverse workforce of high-performing individuals.
• AWS Certification is a plus

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.

Lead AI Engineer

Location: Bengaluru, Hybrid | Type: Full-time

About Newpage Solutions

Newpage Solutions is a global digital health innovation company helping people live longer, healthier lives. We partner with life sciences organisations—which include pharmaceutical, biotech, and healthcare leaders—to build transformative AI and data-driven technologies addressing real-world health challenges.

From strategy and research to UX design and agile development, we deliver and validate impactful solutions using lean, human-centered practices.

We are proud to be a ‘Great Place to Work®’ certified company for the last three consecutive years. We also hold a top Glassdoor rating and are named among the "Top 50 Most Promising Healthcare Solution Providers" by CIOReview.

As an organisation, we foster creativity, continuous learning, and inclusivity, creating an environment where bold ideas thrive and make a measurable difference in people’s lives.

Your Mission

We’re seeking a highly experienced, technically exceptional Lead AI Engineer to architect and deliver next-generation Generative AI and Agentic systems. You will drive end-to-end innovation, from model selection and orchestration design to scalable backend implementation, all while collaborating with cross-functional teams to transform AI research into production-ready solutions.

This is an individual-contributor leadership role for someone who thrives on ownership, fast execution, and technical excellence. You will define the standards for quality, scalability, and innovation across all AI initiatives.

What You’ll Do

Develop AI Applications & Agentic Systems

• Architect, build, and optimise production-grade Generative AI and agentic applications using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, n8n, Pydantic AI or custom orchestration layers integrating with LLMs such as GPT, Claude, Gemini as well as self-hosted LLMs along with MCP integrations.
• Implement Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone, ChromaDB, Weaviate, pgvector, etc.) and search engines such as ElasticSearch / Solr using both TF/IDF BM25-based full-text search and similarity search techniques.
• Implement guardrails, observability, fine-tune and train models for industry or domain-specific use cases.
• Build multi-modal workflows using text, image, voice, and video.
• Design robust prompt & context engineering frameworks to improve accuracy, repeatability, quality, cost, and latency.
• Build supporting microservices and modular backends using Python, JavaScript, or Java aligned with domain-driven design, SOLID principles, OOP, and clean architecture, using various databases including relational, document, Key-Value, Graph, and event-driven systems using Kafka / MSK, SQS, etc.
• Deploy cloud-native applications in hyper-scalers such as AWS / GCP / Azure using containerisation and orchestration with Docker / Kubernetes or serverless architecture.
• Apply industry best engineering practices: TDD, well-structured and clean code with linting, domain-driven design, security-first design (secrets management, rotation, SAST, DAST), comprehensive observability (structured logging, metrics, tracing), containerisation & orchestration (Docker, Kubernetes), automated CI/CD pipelines (GitHub Actions, Jenkins).

AI-Assisted Development, Context Engineering & Innovation

• Use AI-assisted development tools such as Claude Code, GitHub Copilot, Codex, Roo Code, Cursor to accelerate development while maintaining code quality and maintainability.
• Utilise coding assistant tools with native instructions, templates, guides, workflows, sub-agents, and more to create developer workflows that improve development velocity, standardisation, and reliability across AI teams.
• Ensure industry best practices to develop well-structured code that is testable, maintainable, performant, scalable, and secure.
• Partner with Product, Design, and ML teams to translate conceptual AI features into scalable user-facing products.
• Provide technical mentorship and guide team members in system design, architecture reviews, and AI best practices.
• Lead POCs, internal research experiments, and innovation sprints to explore and validate emerging AI techniques.

What You Bring

• 7–12 years of total experience in software development, with at least 3 years in AI/ML systems engineering or Generative AI.
• Experience with cloud-native deployments and services in AWS / GCP / Azure, with the ability to architect distributed systems.
• A ‘no-compromise’ attitude with engineering best practices such as clean code, TDD, containerisation, security, CI/CD, scalability, performance, and cost optimisation.
• Active user of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) with demonstrable experience using structured workflows and sub-agents.
• A deep understanding of LLMs, context engineering approaches, and best practices, with the ability to optimise accuracy, latency, and cost.
• Python or JavaScript experience with strong grasp of OOP, SOLID principles, 12-factor application development, and scalable microservice architecture.
• Proven track record developing and deploying GenAI/LLM-based systems in production.
• Advanced understanding of context engineering, prompt construction, optimisation, and evaluation techniques.
• End-to-end implementation experience using vector databases and retrieval pipelines.
• Experience with GitHub Actions, Docker, Kubernetes, and cloud-native deployments.
• Obsession with clean code, system scalability, and performance optimisation.
• Ability to balance rapid prototyping with long-term maintainability.
• Excel at working independently while collaborating effectively across teams.
• Stay ahead of the curve on new AI models, frameworks, and best practices.
• Have a founder’s mindset and love solving ambiguous, high-impact technical challenges.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical discipline.

Bonus Skills / Experience

• Understanding of MLOps, model serving, scaling, and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker).
• Experience building streaming + batch data ingestion and transformation pipelines (Spark / Airflow / Beam).
• Mobile and front-end web application development experience.

What We Offer

• A people-first culture – Supportive peers, open communication, and a strong sense of belonging.
• Smart, purposeful collaboration – Work with talented colleagues to create technologies that solve meaningful business challenges.
• Balance that lasts – We respect your time and support a healthy integration of work and life.
• Room to grow – Opportunities for learning, leadership, and career development, shaped around you.
• Meaningful rewards – Competitive compensation that recognises both contribution and potential.

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 Description: Applied Scientist

Location: Bangalore / Hybrid / Remote

Company: LodgIQ

Industry: Hospitality / SaaS / Machine Learning

About LodgIQ

Headquartered in New York, LodgIQ delivers a revolutionary B2B SaaS platform to the

travel industry. By leveraging machine learning and artificial intelligence, we enable precise

forecasting and optimized pricing for hotel revenue management. Backed by Highgate

Ventures and Trilantic Capital Partners, LodgIQ is a well-funded, high-growth startup with a

global presence.

About the Role

We are seeking a highly motivated Applied Scientist to join our Data Science team. This

individual will play a key role in enhancing and scaling our existing forecasting and pricing

systems and developing new capabilities that support our intelligent decision-making

platform.

We are looking for team members who: ● Are deeply curious and passionate about applying machine learning to real-world

problems. ● Demonstrate strong ownership and the ability to work independently. ● Excel in both technical execution and collaborative teamwork. ● Have a track record of shipping products in complex environments.

What You’ll Do ● Build, train, and deploy machine learning and operations research models for

forecasting, pricing, and inventory optimization. ● Work with large-scale, noisy, and temporally complex datasets. ● Collaborate cross-functionally with engineering and product teams to move models

from research to production. ● Generate interpretable and trusted outputs to support adoption of AI-driven rate

recommendations. ● Contribute to the development of an AI-first platform that redefines hospitality revenue

management.

Required Qualifications ● Bachelor's or Master’s degree or PhD in Computer Science or related field. ● 3-5 years of hands-on experience in a product-centric company, ideally with full model

lifecycle exposure.

Commented [1]: Leaving note here

Acceptable Degree types - Masters or PhD

Fields

Operations Research

Industrial/Systems Engineering

Computer Science

Applied Mathematics

● Demonstrated ability to apply machine learning and optimization techniques to solve

real-world business problems.

● Proficient in Python and machine learning libraries such as PyTorch, statsmodel,

LightGBM, scikit-learn, XGBoost

● Strong knowledge of Operations Research models (Stochastic optimization, dynamic

programming) and forecasting models (time-series and ML-based).

● Understanding of machine learning and deep learning foundations.

● Translate research into commercial solutions

● Strong written and verbal communication skills to explain complex technical concepts

clearly to cross-functional teams.

● Ability to work independently and manage projects end-to-end.

Preferred Experience

● Experience in revenue management, pricing systems, or demand forecasting,

particularly within the hotel and hospitality domain.

● Applied knowledge of reinforcement learning techniques (e.g., bandits, Q-learning,

model-based control).

● Familiarity with causal inference methods (e.g., DAGs, treatment effect estimation).

● Proven experience in collaborative product development environments, working closely

with engineering and product teams.

Why LodgIQ?

● Join a fast-growing, mission-driven company transforming the future of hospitality.

● Work on intellectually challenging problems at the intersection of machine learning,

decision science, and human behavior.

● Be part of a high-impact, collaborative team with the autonomy to drive initiatives from

ideation to production.

● Competitive salary and performance bonuses.

● For more information, visit https://www.lodgiq.com

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

ML Intern

Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.

JOB OVERVIEW

We are seeking a talented and results-oriented ML Intern to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating assistants of the future. 

The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.

RESPONSIBILITIES:

• Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
• Develop custom evals for AI agents.
• Build and maintain ML pipelines
• Optimize and evaluate ML models to ensure accuracy and performance.
• Define system requirements and integrate ML algorithms into cloud based workflows.
• Write clean, well-documented, and maintainable code following best practices

REQUIREMENTS:

• 1-3+ years of experience in data science, machine learning, or a similar role.
• Demonstrated expertise with python, PyTorch, and TensorFlow.
• Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
• Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
• Has demonstrated experience with Model Context Protocols (MCPs), DsPy, AI Agents, MLOps etc

WHO CAN APPLY:

Only those candidates will be considered who,

• have relevant skills and interests
• can commit full time
• Can show prior work and deployed projects
• can start immediately

Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.

SALARY DETAILS: Commensurate with experience.

JOINING DATE: Immediate

JOB TYPE: Full-time

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

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

We're Hiring: Machine Learning & Data Science Engineer

Location: Gurugram / Bengaluru (Full-time, In-Office)

Salary: Up to ₹2.5 Cr

Preferred Qualifications: PhDs, Tier-1 Grads (IITs, IISc, top global universities)

Join a stealth, VC-backed startup operating across the US, India, and EU, shaping the future of AI-driven Observability utilizing LLMs, Generative AI, and cutting-edge ML technologies. Collaborate with visionary founders experienced in scaling billion-dollar products.

🔍 What You’ll Do:

- Develop advanced time series models for anomaly detection & forecasting

- Create LLM-powered Root Cause Analysis systems employing causal inference & ML techniques

- Innovate using LLMs for enhanced time series comprehension

- Build real-time ML pipelines & scalable MLOps workflows

- Utilize Bayesian methods, causality, counterfactuals, and agent evaluation frameworks

- Handle extensive datasets in Python (TensorFlow, PyTorch, Scikit-Learn, Statsmodels, etc.)

✅ What We’re Looking For:

- Minimum 5 years of experience in ML, time series, and causal analytics

- Proficiency in Python & the ML ecosystem

- In-depth understanding of causal inference, Bayesian statistics, LLMs

- Background in ML Ops, scalable systems, and production deployment

- Additional expertise in Observability, AI agents, or LLM Ops is a plus

💡 Why Join:

- Contribute to building a groundbreaking product from inception

- Tackle real-world impactful challenges alongside a top-tier team

- Engage in a culture that prioritizes ownership, agility, and creativity

Apply here: https://whitetable.ai/form/machine-learning-data-science-engineer-dc784b

Job Overview:

We are looking for a skilled Senior Backend Engineer to join our team. The ideal candidate will have a strong foundation in Java and Spring, with proven experience in building scalable microservices and backend systems. This role also requires familiarity with automation tools, Python development, and working knowledge of AI technologies.

Responsibilities:

• Design, develop, and maintain backend services and microservices.
• Build and integrate RESTful APIs across distributed systems.
• Ensure performance, scalability, and reliability of backend systems.
• Collaborate with cross-functional teams and participate in agile development.
• Deploy and maintain applications on AWS cloud infrastructure.
• Contribute to automation initiatives and AI/ML feature integration.
• Write clean, testable, and maintainable code following best practices.
• Participate in code reviews and technical discussions.

Required Skills:

• 4+ years of backend development experience.
• Strong proficiency in Java and Spring/Spring Boot frameworks.
• Solid understanding of microservices architecture.
• Experience with REST APIs, CI/CD, and debugging complex systems.
• Proficient in AWS services such as EC2, Lambda, S3.
• Strong analytical and problem-solving skills.
• Excellent communication in English (written and verbal).

Good to Have:

• Experience with automation tools like Workato or similar.
• Hands-on experience with Python development.
• Familiarity with AI/ML features or API integrations.
• Comfortable working with US-based teams (flexible hours).

Company name: JPMorgan (JPMC)

Job Category:
 Predictive Science

Location: Parcel 9, Embassy Tech Village, Outer Ring Road, Deverabeesanhalli Village, Varthur Hobli, Bengaluru

Job Schedule: 
Full time

JOB DESCRIPTION

JPMC is hiring the best talents to join the growing Asset and Wealth Management AI team. We are executing like a startup and building next-generation technology that combines JPMC unique data and full-service advantage to develop high impact AI applications and platforms in the financial services industry. We are looking for hands-on ML Engineering leader and expert who is excited about the opportunity. 

As a senior ML and GenAI engineer, you will play a lead role as a senior member of our global team. Your responsibilities will entail hands on development of high-impact business solutions through data analysis, developing cutting edge ML and LLM models, and deploying these models to production environments on AWS or Azure. 

You'll combine your years of proven development expertise with a never-ending quest to create innovative technology through solid engineering practices. Your passion and experience in one or more technology domains will help solve complex business problems to serve our Private Bank clients. As a constant learner and early adopter, you’re already embracing leading-edge technologies and methodologies; your example encourages others to follow suit. 

 Job responsibilities 

• Hands-on architecture and implementation of lighthouse ML and LLM-powered solutions 

• Close partnership with peers in a geographically dispersed team and colleagues across organizational lines 

• Collaborate across JPMorgan AWM’s lines of business and functions to accelerate adoption of common AI capabilities 

• Design and implement highly scalable and reliable data processing pipelines and deploy model inference services. 

• Deploy solutions into public cloud infrastructure 

• Experiment, develop and productionize high quality machine learning models, services, and platforms to make a huge technology and business impact 

 Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience

• MS in Computer Science, Statistics, Mathematics or Machine Learning. 

• Development experience, along with hands-on Machine Learning Engineering 

• Proven leadership capacity, including new AI/ML idea generation and GenAI-based solutions 

• Solid Python programming skills required; with other high-performance language such as Go a big plus 

• Expert knowledge of one of the cloud computing platforms preferred: Amazon Web Services (AWS), Azure, Kubernetes. 

• Experience in using LLMs (OpenAI, Claude or other models) to solve business problems, including full workflow toolset, such as tracing, evaluations and guardrails. Understanding of LLM fine-tuning and inference a plus 

• Knowledge of data pipelines, both batch and real-time data processing on both SQL (such as Postgres) and NoSQL stores (such as OpenSearch and Redis) 

• Expertise in application, data, and infrastructure architecture disciplines 

• Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. 

• Excellent communication skills and ability to communicate with senior technical and business partners 

 Preferred qualifications, capabilities, and skills

• Expert in at least one of the following areas: Natural Language Processing, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. 

• Knowledge of machine learning frameworks: Pytorch, Keras, MXNet, Scikit-Learn 

• Understanding of finance or wealth management businesses is an added advantage 

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

ABOUT THE TEAM

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

Job Description – Machine Learning Expert

Role: Machine Learning Expert

Experience: 6+ Years

Location: Bangalore

Education: B.Tech Degree (Computer Science / Information Technology / Data Science / related fields)

Work Mode: Hybrid – 3 Days Office + 3 Days Work from Home

Interview Mode: Candidate must be willing to attend Face-to-Face (F2F) L2 round at Bangalore location

About the Role

We are seeking a highly skilled Machine Learning Expert with a strong background in building, training, and deploying AI/ML models. The ideal candidate will bring hands-on expertise in designing intelligent systems that leverage advanced algorithms, deep learning, and data-driven insights to solve complex business challenges.

Key Responsibilities

• Develop and implement machine learning and deep learning models for real-world business use cases.
• Perform data cleaning, preprocessing, feature engineering, and model optimization.
• Research, design, and apply state-of-the-art ML techniques across domains such as NLP, Computer Vision, or Predictive Analytics.
• Collaborate with data engineers and software developers to ensure seamless end-to-end ML solution deployment.
• Deploy ML models to production environments and monitor performance for scalability and accuracy.
• Stay updated with the latest advancements in Artificial Intelligence and Machine Learning frameworks.
• 
  

Required Skills & Qualifications

• B.Tech degree in Computer Science, Information Technology, Data Science, or related discipline.
• 6+ years of hands-on experience in Machine Learning, Artificial Intelligence, and Deep Learning.
• Strong expertise in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras.
• Solid foundation in mathematics, statistics, algorithms, and probability.
• Experience in working with NLP, Computer Vision, Recommendation Systems, or Predictive Modeling.
• Knowledge of cloud platforms (AWS / GCP / Azure) for model deployment.
• Familiarity with MLOps tools and practices for lifecycle management.
• Excellent problem-solving skills and the ability to work in a collaborative environment.
• 
  

Preferred Skills (Good to Have)

• Experience with Big Data frameworks (Hadoop, Spark).
• Exposure to Generative AI, LLMs (Large Language Models), and advanced AI research.
• Contributions to open-source projects, publications, or patents in AI/ML.
• 
  

Work Mode & Interview Process

• Hybrid Model: 3 days in office (Bangalore) + 3 days remote.
• Interview: Candidate must be available for Face-to-Face L2 interview at Bangalore location.

Senior Cloud & ML Infrastructure Engineer

Location: Bangalore / Bengaluru, Hyderabad, Pune, Mumbai, Mohali, Panchkula, Delhi

Experience: 6–10+ Years

Night Shift - 9 pm to 6 am

About the Role:

We’re looking for a Senior Cloud & ML Infrastructure Engineer to lead the design,scaling, and optimization of cloud-native machine learning infrastructure. This role is ideal forsomeone passionate about solving complex platform engineering challenges across AWS, witha focus on model orchestration, deployment automation, and production-grade reliability. You’llarchitect ML systems at scale, provide guidance on infrastructure best practices, and work cross-functionally to bridge DevOps, ML, and backend teams.

Key Responsibilities:

● Architect and manage end-to-end ML infrastructure using SageMaker, AWS StepFunctions, Lambda, and ECR

● Design and implement multi-region, highly-available AWS solutions for real-timeinference and batch processing

● Create and manage IaC blueprints for reproducible infrastructure using AWS CDK

● Establish CI/CD practices for ML model packaging, validation, and drift monitoring

● Oversee infrastructure security, including IAM policies, encryption at rest/in-transit, andcompliance standards

● Monitor and optimize compute/storage cost, ensuring efficient resource usage at scale

● Collaborate on data lake and analytics integration

● Serve as a technical mentor and guide AWS adoption patterns across engineeringteams

Required Skills:

● 6+ years designing and deploying cloud infrastructure on AWS at scale

● Proven experience building and maintaining ML pipelines with services like SageMaker,ECS/EKS, or custom Docker pipelines

● Strong knowledge of networking, IAM, VPCs, and security best practices in AWS

● Deep experience with automation frameworks, IaC tools, and CI/CD strategies

● Advanced scripting proficiency in Python, Go, or Bash

● Familiarity with observability stacks (CloudWatch, Prometheus, Grafana)

Nice to Have:

● Background in robotics infrastructure, including AWS IoT Core, Greengrass, or OTA deployments

● Experience designing systems for physical robot fleet telemetry, diagnostics, and control

● Familiarity with multi-stage production environments and robotic software rollout processes

● Competence in frontend hosting for dashboard or API visualization

● Involvement with real-time streaming, MQTT, or edge inference workflows

● Hands-on experience with ROS 2 (Robot Operating System) or similar robotics frameworks, including launch file management, sensor data pipelines, and deployment to embedded Linux devices

🚀 We’re Hiring: Senior Cloud & ML Infrastructure Engineer 🚀

We’re looking for an experienced engineer to lead the design, scaling, and optimization of cloud-native ML infrastructure on AWS.

If you’re passionate about platform engineering, automation, and running ML systems at scale, this role is for you.

What you’ll do:

🔹 Architect and manage ML infrastructure with AWS (SageMaker, Step Functions, Lambda, ECR)

🔹 Build highly available, multi-region solutions for real-time & batch inference

🔹 Automate with IaC (AWS CDK, Terraform) and CI/CD pipelines

🔹 Ensure security, compliance, and cost efficiency

🔹 Collaborate across DevOps, ML, and backend teams

What we’re looking for:

✔️ 6+ years AWS cloud infrastructure experience

✔️ Strong ML pipeline experience (SageMaker, ECS/EKS, Docker)

✔️ Proficiency in Python/Go/Bash scripting

✔️ Knowledge of networking, IAM, and security best practices

✔️ Experience with observability tools (CloudWatch, Prometheus, Grafana)

✨ Nice to have: Robotics/IoT background (ROS2, Greengrass, Edge Inference)

📍 Location: Bengaluru, Hyderabad, Mumbai, Pune, Mohali, Delhi

5 days working, Work from Office

Night shifts: 9pm to 6am IST

👉 If this sounds like you (or someone you know), let’s connect!

Apply here:

Job Title: Data Scientist

Location: Bangalore (Hybrid/On-site depending on project needs)

About the Role

We are seeking a highly skilled Data Scientist to join our team in Bangalore. In this role, you will take ownership of data science components across client projects, build production-ready ML and GenAI-powered applications, and mentor junior team members. You will collaborate with engineering teams to design and deploy impactful solutions that leverage cutting-edge machine learning and large language model technologies.

Key Responsibilities

ML & Data Science

• Develop, fine-tune, and evaluate ML models (classification, regression, clustering, recommendation systems).
• Conduct exploratory data analysis, preprocessing, and feature engineering.
• Ensure model reproducibility, scalability, and alignment with business objectives.

GenAI & LLM Applications

• Prototype and design solutions leveraging LLMs (OpenAI, Claude, Mistral, Llama).
• Build RAG (Retrieval-Augmented Generation) pipelines, prompt templates, and evaluation frameworks.
• Integrate LLMs with APIs and vector databases (Pinecone, FAISS, Weaviate).

Product & Engineering Collaboration

• Partner with engineering teams to productionize ML/GenAI models.
• Contribute to API development, data pipelines, technical documentation, and client presentations.

Team & Growth

• Mentor junior data scientists and review technical contributions.
• Stay up to date with the latest ML & GenAI research and tools; share insights across the team.

Required Skills & Qualifications

• 4.5–9 years of applied data science experience.
• Strong proficiency in Python and ML libraries (scikit-learn, XGBoost, LightGBM).
• Hands-on experience with LLM APIs (OpenAI, Cohere, Claude) and frameworks (LangChain, LlamaIndex).
• Strong SQL, data wrangling, and analysis skills (pandas, NumPy).
• Experience working with APIs, Git, and cloud platforms (AWS/GCP).

Good-to-Have

• Deployment experience with FastAPI, Docker, or serverless frameworks.
• Familiarity with MLOps tools (MLflow, DVC).
• Experience working with embeddings, vector databases, and similarity search.

Proven experience as a Data Scientist or similar role with relevant experience of at least 4 years and total experience 6-8 years.

· Technical expertiseregarding data models, database design development, data mining and segmentation techniques

· Strong knowledge of and experience with reporting packages (Business Objects and likewise), databases, programming in ETL frameworks

· Experience with data movement and management in the Cloud utilizing a combination of Azure or AWS features

· Hands on experience in data visualization tools – Power BI preferred

· Solid understanding of machine learning

· Knowledge of data management and visualization techniques

· A knack for statistical analysis and predictive modeling

· Good knowledge of Python and Matlab

· Experience with SQL and NoSQL databases including ability to write complex queries and procedures

About the Role

We are seeking an innovative Data Scientist specializing in Natural Language Processing (NLP) to join our technology team in Bangalore. The ideal candidate will harness the power of language models and document extraction techniques to transform legal information into accessible, actionable insights for our clients.

Responsibilities

• Develop and implement NLP solutions to automate legal document analysis and extraction
• Create and optimize prompt engineering strategies for large language models
• Design search functionality leveraging semantic understanding of legal documents
• Build document extraction pipelines to process unstructured legal text data
• Develop data visualizations using PowerBI and Tableau to communicate insights
• Collaborate with product and legal teams to enhance our tech-enabled services
• Continuously improve model performance and user experience

Requirements

• Bachelor's degree in relevant field
• 1-5 years of professional experience in data science, with focus on NLP applications
• Demonstrated experience working with LLM APIs (e.g., OpenAI, Anthropic, )
• Proficiency in prompt engineering and optimization techniques
• Experience with document extraction and information retrieval systems
• Strong skills in data visualization tools, particularly PowerBI and Tableau
• Excellent programming skills in Python and familiarity with NLP libraries
• Strong understanding of legal terminology and document structures (preferred)
• Excellent communication skills in English

What We Offer

• Competitive salary and benefits package
• Opportunity to work at India's largest legal tech company
• Professional growth in the fast-evolving legal technology sector
• Collaborative work environment with industry experts
• Modern office located in Bangalore
• Flexible work arrangements

Qualified candidates are encouraged to apply with a resume highlighting relevant experience with NLP, prompt engineering, and data visualization tools.

Location: Bangalore, India

3+ years of experience in cybersecurity, with a focus on application and cloud security.

· Proficiency in security tools such as Burp Suite, Metasploit, Nessus, OWASP ZAP, and SonarQube.

· Familiarity with data privacy regulations (GDPR, CCPA) and best practices.

· Basic knowledge of AI/ML security frameworks and tools.

Role Overview:

Zolvit is looking for a highly skilled and self-driven Lead Machine Learning Engineer / Lead Data Scientist to lead the design and development of scalable, production-grade ML systems. This role is ideal for someone who thrives on solving complex problems using data, is deeply passionate about machine learning, and has a strong understanding of both classical techniques and modern AI systems like Large Language Models (LLMs).

You will work closely with engineering, product, and business teams to identify impactful ML use cases, build data pipelines, design training workflows, and ensure the deployment of robust, high-performance models at scale.

Key Responsibilities:

● Design and implement scalable ML systems, from experimentation to deployment.

● Build and maintain end-to-end data pipelines for data ingestion, preprocessing, feature engineering, and monitoring.

● Lead the development and deployment of ML models across a variety of use cases — including classical ML and LLM-based applications like summarization, classification, document understanding, and more.

● Define model training and evaluation pipelines, ensuring reproducibility and performance tracking.

● Apply statistical methods to interpret data, validate assumptions, and inform modeling decisions.

● Collaborate cross-functionally with engineers, data analysts, and product managers to solve high-impact business problems using ML.

● Ensure proper MLOps practices are in place for model versioning, monitoring, retraining, and performance management.

● Keep up-to-date with the latest advancements in AI/ML, and actively evaluate and incorporate LLM capabilities and frameworks into solutions.

● Mentor junior ML engineers and data scientists, and help scale the ML function across the organization.

Required Qualifications:

● 7+ years of hands-on experience in ML/AI, building real-world ML systems at scale.

● Proven experience with classical ML algorithms (e.g., regression, classification,

clustering, ensemble models).

● Deep expertise in modern LLM frameworks (e.g., OpenAI, HuggingFace, LangChain)

and their integration into production workflows.

● Strong experience with Python, and frameworks such as Scikit-learn, TensorFlow,

PyTorch, or equivalent.

● Solid background in statistics and the ability to apply statistical thinking to real-world

problems.

● Experience with data engineering tools and platforms (e.g., Spark, Airflow, SQL,

Pandas, AWS Glue, etc.).

● Familiarity with cloud services (AWS preferred) and containerization tools (Docker,

Kubernetes) is a plus.

● Strong communication and leadership skills, with experience mentoring and guiding

junior team members.

● Self-starter attitude with a bias for action and ability to thrive in fast-paced environments.

● Master’s degree in Machine Learning, Artificial Intelligence, Statistics, or a related

field is preferred.

Preferred Qualifications:

● Experience deploying ML systems in microservices or event-driven architectures.

● Hands-on experience with vector databases, embeddings, and retrieval-augmented

generation (RAG) systems.

● Understanding of Responsible AI principles and practices.

Why Join Us?

● Lead the ML charter in a mission-driven company solving real-world challenges.

● Work on cutting-edge LLM use cases and platformize ML capabilities for scale.

● Collaborate with a passionate and technically strong team in a high-impact environment.

● Competitive compensation, flexible working model, and ample growth opportunities.

Technical Skills – Must have  

 Lead the design and development of AI-driven test automation frameworks and solutions.

 Collaborate with stakeholders (e.g., product managers, developers, data scientists) to understand testing requirements and identify areas where AI automation can be effectively implemented.

 Develop and implement test automation strategies for AI-based systems, encompassing various aspects like data generation, model testing, and performance evaluation.

 Evaluate and select appropriate tools and technologies for AI test automation, including AI frameworks, testing tools, and automation platforms.

 Define and implement best practices for AI test automation, covering areas like code standards, test case design, test data management, and ethical considerations.

 Lead and mentor a team of test automation engineers in designing, developing, and executing AI test automation solutions.

 Collaborate with development teams to ensure the testability of AI models and systems, providing guidance and feedback throughout the development lifecycle.

 Analyze test results and identify areas for improvement in the AI automation process, continuously optimizing testing effectiveness and efficiency.

 Stay up-to-date with the latest advancements and trends in AI and automation technologies, actively adapting and implementing new knowledge to enhance testing capabilities.

 Knowledge in Generative AI and Conversational AI for implementation in test automation strategies is highly desirable.

 Proficiency in programming languages commonly used in AI, such as Python, Java, or R.

 Knowledge on AI frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.

 Familiarity with testing methodologies and practices, including Agile and DevOps.

 Working experience on Python/Java and Selenium also knowledge in prompt engineering.

Senior Data Engineer Job Description

Overview

The Senior Data Engineer will design, develop, and maintain scalable data pipelines and

infrastructure to support data-driven decision-making and advanced analytics. This role requires deep

expertise in data engineering, strong problem-solving skills, and the ability to collaborate with

cross-functional teams to deliver robust data solutions.

Key Responsibilities

Data Pipeline Development: Design, build, and optimize scalable, secure, and reliable data

pipelines to ingest, process, and transform large volumes of structured and unstructured data.

Data Architecture: Architect and maintain data storage solutions, including data lakes, data

warehouses, and databases, ensuring performance, scalability, and cost-efficiency.

Data Integration: Integrate data from diverse sources, including APIs, third-party systems,

and streaming platforms, ensuring data quality and consistency.

Performance Optimization: Monitor and optimize data systems for performance, scalability,

and cost, implementing best practices for partitioning, indexing, and caching.

Collaboration: Work closely with data scientists, analysts, and software engineers to

understand data needs and deliver solutions that enable advanced analytics, machine

learning, and reporting.

Data Governance: Implement data governance policies, ensuring compliance with data

security, privacy regulations (e.g., GDPR, CCPA), and internal standards.

Automation: Develop automated processes for data ingestion, transformation, and validation

to improve efficiency and reduce manual intervention.

Mentorship: Guide and mentor junior data engineers, fostering a culture of technical

excellence and continuous learning.

Troubleshooting: Diagnose and resolve complex data-related issues, ensuring high

availability and reliability of data systems.

Required Qualifications

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science,

or a related field.

Experience: 5+ years of experience in data engineering or a related role, with a proven track

record of building scalable data pipelines and infrastructure.

Technical Skills:

Proficiency in programming languages such as Python, Java, or Scala.

Expertise in SQL and experience with NoSQL databases (e.g., MongoDB, Cassandra).

Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services

(e.g., Redshift, BigQuery, Snowflake).

Hands-on experience with ETL/ELT tools (e.g., Apache Airflow, Talend, Informatica) and

data integration frameworks.

Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) and distributed

systems.

Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a

plus.

Soft Skills:

Excellent problem-solving and analytical skills.

Strong communication and collaboration abilities.

Ability to work in a fast-paced, dynamic environment and manage multiple priorities.

Certifications (optional but preferred): Cloud certifications (e.g., AWS Certified Data Analytics,

Google Professional Data Engineer) or relevant data engineering certifications.

Preferred Qualifica

Experience with real-time data processing and streaming architectures.

Familiarity with machine learning pipelines and MLOps practices.

Knowledge of data visualization tools (e.g., Tableau, Power BI) and their integration with data

pipelines.

Experience in industries with high data complexity, such as finance, healthcare, or

e-commerce.

Work Environment

Location: Hybrid/Remote/On-site (depending on company policy).

Team: Collaborative, cross-functional team environment with data scientists, analysts, and

business stakeholders.

Hours: Full-time, with occasional on-call responsibilities for critical data systems.

What You will do:

● Create beautiful software experiences for our clients using design thinking, lean, and agile methodology.

● Work on software products designed from scratch using the latest cutting-edge technologies, platforms, and languages such as NodeJS, JavaScript.

● Work in a dynamic, collaborative, transparent, non-hierarchical culture.

● Work in collaborative, fast-paced,d and value-driven teams to build innovative customer experiences for our clients.

● Help to grow the next generation of developers and have a positive impact on the industry.

Basic Qualifications :

● Experience: 4+ years.

● Hands-on development experience with a broad mix of languages such as NodeJS,

● Server-side development experience, mainly in NodeJS, can be considerable

● UI development experience in AngularJS

● Passion for software engineering and following the best coding concepts .

● Good to great problem-solving and communication skills.

Nice to have Qualifications:

● Product and customer-centric mindset.

● Great OO skills, including design patterns.

● Experience with devops, continuous integration & deployment.

● Exposure to big data technologies, Machine Learning, and NLP will be a plus.

What You will do:

● Play the role of Data Analyst / ML Engineer

● Collection, cleanup, exploration and visualization of data

● Perform statistical analysis on data and build ML models

● Implement ML models using some of the popular ML algorithms

● Use Excel to perform analytics on large amounts of data

● Understand, model and build to bring actionable business intelligence out of data that is available in different formats

● Work with data engineers to design, build, test and monitor data pipelines for ongoing business operations







Basic Qualifications:

● Experience: 4+ years.

● Hands-on development experience playing the role of Data Analyst and/or ML Engineer.

● Experience in working with excel for data analytics

● Experience with statistical modelling of large data sets

● Experience with ML models and ML algorithms

● Coding experience in Python







Nice to have Qualifications:

● Experience with wide variety of tools used in ML

● Experience with Deep learning







Benefits:

● Competitive salary.

● Hybrid work model.

● Learning and gaining experience rapidly.

● Reimbursement for basic working set up at home.

● Insurance (including a top up insurance for COVID

Responsibilities

• Model Development and Optimization: Design, build, and deploy NLP models, including transformer models (e.g., BERT, GPT, T5) and other SOTA architectures, as well as traditional machine learning algorithms (e.g., SVMs, Logistic Regression) for specific applications.

• Data Processing and Feature Engineering: Develop robust pipelines for text preprocessing, feature extraction, and data augmentation for structured and unstructured data.

• Model Fine-Tuning and Transfer Learning:

Fine-tune large language models for specific applications, leveraging transfer learning techniques, domain adaptation, and a mix of deep learning and traditional ML models.

• Performance Optimization: Optimize model performance for scalability and latency, applying techniques such as quantization, ONNX formats etc.

• Research and Innovation: Stay updated with the latest research in NLP, Deep Learning, and Generative AI, applying innovative solutions and techniques (e.g., RAG applications, Prompt engineering, Self-supervised learning).

• Stakeholder Communication: Collaborate with stakeholders to gather requirements, conduct due diligence, and communicate project updates effectively, ensuring alignment between technical solutions and business goals.

• Evaluation and Testing: Establish metrics, benchmarks, and methodologies for model evaluation, including cross-validation, and error analysis, ensuring models meet accuracy, fairness, and reliability standards. • Deployment and Monitoring: Oversee the deployment of NLP models in production, ensuring seamless integration, model monitoring, and retraining processes. 

JioTesseract, a digital arm of Reliance Industries, is India's leading and largest AR/VR organization with the mission to democratize mixed reality for India and the world. We make products at the cross of hardware, software, content and services with focus on making India the leader in spatial computing. We specialize in creating solutions in AR, VR and AI, with some of our notable products such as JioGlass, JioDive, 360 Streaming, Metaverse, AR/VR headsets for consumers and enterprise space.

Mon-fri role, In office, with excellent perks and benefits!

Position Overview

We are seeking a Software Architect to lead the design and development of high-performance robotics and AI software stacks utilizing NVIDIA technologies. This role will focus on defining scalable, modular, and efficient architectures for robot perception, planning, simulation, and embedded AI applications. You will collaborate with cross-functional teams to build next-generation autonomous systems 9

Key Responsibilities:

1. System Architecture & Design

● Define scalable software architectures for robotics perception, navigation, and AI-driven decision-making.

● Design modular and reusable frameworks that leverage NVIDIA’s Jetson, Isaac ROS, Omniverse, and CUDA ecosystems.

● Establish best practices for real-time computing, GPU acceleration, and edge AI inference.

2. Perception & AI Integration

● Architect sensor fusion pipelines using LIDAR, cameras, IMUs, and radar with DeepStream, TensorRT, and ROS2.

● Optimize computer vision, SLAM, and deep learning models for edge deployment on Jetson Orin and Xavier.

● Ensure efficient GPU-accelerated AI inference for real-time robotics applications.

3. Embedded & Real-Time Systems

● Design high-performance embedded software stacks for real-time robotic control and autonomy.

● Utilize NVIDIA CUDA, cuDNN, and TensorRT to accelerate AI model execution on Jetson platforms.

● Develop robust middleware frameworks to support real-time robotics applications in ROS2 and Isaac SDK.

4. Robotics Simulation & Digital Twins

● Define architectures for robotic simulation environments using NVIDIA Isaac Sim & Omniverse.

● Leverage synthetic data generation (Omniverse Replicator) for training AI models.

● Optimize sim-to-real transfer learning for AI-driven robotic behaviors.

5. Navigation & Motion Planning

● Architect GPU-accelerated motion planning and SLAM pipelines for autonomous robots.

● Optimize path planning, localization, and multi-agent coordination using Isaac ROS Navigation.

● Implement reinforcement learning-based policies using Isaac Gym.

6. Performance Optimization & Scalability

● Ensure low-latency AI inference and real-time execution of robotics applications.

● Optimize CUDA kernels and parallel processing pipelines for NVIDIA hardware.

● Develop benchmarking and profiling tools to measure software performance on edge AI devices.

Required Qualifications:

● Master’s or Ph.D. in Computer Science, Robotics, AI, or Embedded Systems.

● Extensive experience (7+ years) in software development, with at least 3-5 years focused on architecture and system design, especially for robotics or embedded systems.

● Expertise in CUDA, TensorRT, DeepStream, PyTorch, TensorFlow, and ROS2.

● Experience in NVIDIA Jetson platforms, Isaac SDK, and GPU-accelerated AI.

● Proficiency in programming languages such as C++, Python, or similar, with deep understanding of low-level and high-level design principles.

● Strong background in robotic perception, planning, and real-time control.

● Experience with cloud-edge AI deployment and scalable architectures.

Preferred Qualifications

● Hands-on experience with NVIDIA DRIVE, NVIDIA Omniverse, and Isaac Gym

● Knowledge of robot kinematics, control systems, and reinforcement learning

● Expertise in distributed computing, containerization (Docker), and cloud robotics

● Familiarity with automotive, industrial automation, or warehouse robotics

● Experience designing architectures for autonomous systems or multi-robot systems.

● Familiarity with cloud-based solutions, edge computing, or distributed computing for robotics

● Experience with microservices or service-oriented architecture (SOA)

● Knowledge of machine learning and AI integration within robotic systems

● Knowledge of testing on edge devices with HIL and simulations (Isaac Sim, Gazebo, V-REP etc.)

Link to apply- https://tally.so/r/w8RpLk

About Us

At GreenStitch, we are on a mission to revolutionise the fashion and textile industry through cutting-edge climate-tech solutions. We are looking for a highly skilled Data Scientist-I with expertise in NLP and Deep Learning to drive innovation in our data-driven applications. This role requires a strong foundation in AI/ML, deep learning, and software engineering to develop impactful solutions aligned with our sustainability and business objectives.

The ideal candidate demonstrates up-to-date expertise in Deep Learning and NLP and applies it to the development, execution, and improvement of applications. This role involves supporting and aligning efforts to meet both customer and business needs.

You will play a key role in building strong relationships with stakeholders, identifying business challenges, and implementing AI-driven solutions. You should be adaptable to competing demands, organisational changes, and new responsibilities while upholding GreenStitch’s mission, values, and ethical standards.

What You’ll Do:

• AI-Powered Applications: Build and deploy AI-driven applications leveraging Generative AI and NLP to enhance user experience and operational efficiency.
• Model Development: Design and implement deep learning models and machine learning pipelines to solve complex business challenges.
• Cross-Functional Collaboration: Work closely with product managers, engineers, and business teams to identify AI/ML opportunities.
• Innovation & Experimentation: Stay up-to-date with the latest AI/ML advancements, rapidly prototype solutions, and iterate on ideas for continuous improvement.
• Scalability & Optimisation: Optimise AI models for performance, scalability, and real-world impact, ensuring production readiness.
• Knowledge Sharing & Thought Leadership: Contribute to publications, patents, and technical forums; represent GreenStitch in industry and academic discussions.
• Compliance & Ethics: Model compliance with company policies and ensure AI solutions align with ethical standards and sustainability goals.
• Communication: Translate complex AI/ML concepts into clear, actionable insights for business stakeholders.

What You’ll Bring:

• Education: Bachelors/Master’s degree in Data Science, Computer Science, AI, or a related field.
• Experience: 1-3 years of hands-on experience in AI/ML, NLP, and Deep Learning.
• Technical Expertise: Strong knowledge of transformer-based models (GPT, BERT, etc.), deep learning frameworks (TensorFlow, PyTorch), and cloud platforms (Azure, AWS, GCP).
• Software Development: Experience in Python, Java, or similar languages, and familiarity with MLOps tools.
• Problem-Solving: Ability to apply AI/ML techniques to real-world challenges with a data-driven approach.
• Growth Mindset: Passion for continuous learning and innovation in AI and climate-tech applications.
• Collaboration & Communication: Strong ability to work with cross-functional teams, communicate complex ideas, and drive AI adoption.

Why GreenStitch?

GreenStitch is at the forefront of climate-tech innovation, helping businesses in the fashion and textile industry reduce their environmental footprint. By joining us, you will:

• Work on high-impact AI projects that contribute to sustainability and decarbonisation.
• Be part of a dynamic and collaborative team committed to making a difference.
• Enjoy a flexible, hybrid work model that supports professional growth and work-life balance.
• Receive competitive compensation and benefits, including healthcare, parental leave, and learning opportunities.

Location: Bangalore(India)

Employment Type: Full Time, Permanent

Industry Type: Climate-Tech / Fashion-Tech

Department: Data Science & Machine Learning

Join us in shaping the future of sustainable fashion with cutting-edge AI solutions! 🚀

Level of skills and experience:

5 years of hands-on experience in using Python, Spark,Sql.

Experienced in AWS Cloud usage and management.

Experience with Databricks (Lakehouse, ML, Unity Catalog, MLflow).

Experience using various ML models and frameworks such as XGBoost, Lightgbm, Torch.

Experience with orchestrators such as Airflow and Kubeflow.

Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).

Fundamental understanding of Parquet, Delta Lake and other data file formats.

Proficiency on an IaC tool such as Terraform, CDK or CloudFormation.

Strong written and verbal English communication skill and proficient in communication with non-technical stakeholderst

We are seeking a Senior Data Scientist with hands-on experience in Generative AI (GenAI) and Large Language Models (LLM). The ideal candidate will have expertise in building, fine-tuning, and deploying LLMs, as well as managing the lifecycle of AI models through LLMOps practices. You will play a key role in driving AI innovation, developing advanced algorithms, and optimizing model performance for various business applications.

Key Responsibilities:

• Develop, fine-tune, and deploy Large Language Models (LLM) for various business use cases.
• Implement and manage the operationalization of LLMs using LLMOps best practices.
• Collaborate with cross-functional teams to integrate AI models into production environments.
• Optimize and troubleshoot model performance to ensure high accuracy and scalability.
• Stay updated with the latest advancements in Generative AI and LLM technologies.

Required Skills and Qualifications:

• Strong hands-on experience with Generative AI, LLMs, and NLP techniques.
• Proven expertise in LLMOps, including model deployment, monitoring, and maintenance.
• Proficiency in programming languages like Python and frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Solid understanding of AI/ML algorithms and model optimization.