76 Machine Learning (ML) Jobs in Pune | Machine Learning (ML) Job openings in Pune

About Us: The Next Generation of WealthTech  

We're Cambridge Wealth, an award-winning force in mutual fund distribution and Fintech. We're not just moving money; we're redefining wealth management for everyone from retail investors to ultra-HNIs (including the NRI segment). Our brand is synonymous with excellence, backed by accolades from the BSE and top Mutual Fund houses.

If you thrive on building high-performance, scalable systems that drive real-world financial impact, you'll feel right at home. Join us in Pune to build the future of finance.

[Learn more: www.cambridgewealth.in]

The Role: Engineering Meets Team Meets Customer

We're looking for an experienced, hands-on Tech Catalyst to accelerate our product innovation. This isn't just a coding job; it's a chance to blend deep backend expertise with product strategy. You will be the engine driving rapid, data-driven product experiments, leveraging AI and Machine Learning to create smart, personalized financial solutions. You'll lead by example, mentoring a small, dedicated team and ensuring technical excellence and rapid deployment in the high-stakes financial domain.

Key Impact Areas: Ship Fast, Break Ground  

1. Backend & AI/ML Innovation  

• Rapid Prototyping: Design and execute quick, iterative experiments to validate new features and market hypotheses, moving from concept to production in days, not months.
• AI-Powered Features: Build scalable Python-based backend services that integrate AI/ML models to enhance customer profiling, portfolio recommendation, and risk analysis.
• System Architecture: Own the performance, stability, and scalability of our core fintech platform, implementing best practices in modern backend development.

2. Product Leadership & Execution  

• Agile Catalyst: Drive and optimize Agile sprints, ensuring clear technical milestones, efficient resource allocation, backlog grooming and maintaining a laser focus on preventing scope creep.
• Mentorship & Management: Provide technical guidance and mentorship to a team of developers, fostering a culture of high performance, code quality, and continuous learning.
• Domain Alignment: Translate complex financial requirements and market insights into precise, actionable technical specifications and seamless user stories.
• Problem Solver: Proactively identify and resolve technical and process bottlenecks, acting as the ultimate problem solver for the engineering and product teams.

3. Financial Domain Expertise  

• High-Value Delivery: Apply deep knowledge of the mutual fund and broader fintech landscape to inform product decisions, ensuring our solutions are compliant, competitive, and truly valuable to our clients.
• Risk & Security: Proactively architect solutions with security and financial risk management baked in from the ground up, protecting client data and assets.

Your Tech Stack & Experience  

The Must-Haves  

• Mindset: A verifiable track record as a proactive First Principle Problem Solver with an intense Passion to Ship production-ready features frequently.
• Startup Experience: Familiarity with the pace and intensity of a fast-iterating environment.
• Customer Empathy: Keeps the customer's experience in mind at all times.
• Team Leadership: Experience in leading, mentoring, or managing a small development team, driving technical excellence and project delivery.
• Systems Thinker: Diagnoses and solves problems by viewing the organization as an interconnected system to anticipate broad impacts and develop holistic, strategic solutions.
• Backend Powerhouse: 2+ years of professional experience with a strong focus on backend development.
• Python Guru: Expert proficiency in Python and related frameworks (e.g., Django, Flask) for building robust, scalable APIs and services.
• AI/ML Integration: Proven ability to leverage and integrate AI/ML models into production-level applications.
• Data Driven: Expert in SQL for complex data querying, analysis, and ETL processes.
• Financial Domain Acumen:Strong, demonstrable knowledge of financial products, especially mutual funds, wealth management, and key fintech metrics.

Nice-to-Haves  

• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Familiarity with Zoho Analytics, Zoho CRM and Zoho Deluge
• Familiarity with modern data analysis tools and visualization platforms (e.g., Mixpanel, Tableau, or custom dashboard tools).
• Understanding of Mutual Fund, AIF, PMS operations

Ready to Own the Backend and Shape Finance?  

This is where your code meets the capital market. If you’re a Fintech-savvy Python expert ready to lead a team and build a scalable platform in Pune, we want to talk.

Apply now to join our award-winning, forward-thinking team.

Our High-Velocity Hiring Process:  

• You Apply & Engage: Quick application and a few insightful questions. (5 min)
• Online Tech Challenge: Prove your tech mettle. (90 min)
• People Sync: A focused call to understand if there is cultural and value alignment. (30 min)
• Deep Dive Technical Interview: Discuss architecture and projects with our senior engineers. (1 hour)
• Founder's Vision Interview: Meet the leadership and discuss your impact. (1 hour)
• Offer & Onboarding: Reference and BGV check follow the successful offer.

What are you building right now that you're most proud of?

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field  
• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

Greetings!

Hiring For Large Product Based Company!

Role- Mlops Engineer

Experience- 8-12 years

Location- Pune, Nagpur

JD-

• 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering  
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure  

Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn  

Hiring for Junior AI Engineer

Exp : 4 - 6 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune WFO

Skills :

- Min 3 years strong programming experience in Python is a MUST

- Min 2 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

- Experience with cloud platforms (AWS/Azure/GCP)

Bachelor’s degree in Engineering, Computer Science, or a related discipline

• 8+ years of experience in project or programme management

• 3+ years of experience delivering AI, Machine Learning, Data, or Analytics programmes

• PMP, Agile, Scrum, or equivalent certification preferred

Title                                 : Senior AI Platform / MLOps Engineer

Experience                    : 6+ years

Work type                      : Chennai - Work from Office/other locations - Remote

Employment Type      : Full Time

Notice Period              : Immediate

Work Day                     :Mon to Fri

Key Responsibilities:

• Install, configure and operate OpenShift, NVIDIA GPU operator, OpenShift AI, and NIM microservices on 12× RTX PRO 6000 across two servers; single-node and HA control-plane topologies
• Serving configuration and tuning: quantized model deployment (FP8/FP4), replica balancing, batching, KV-cache and context management
• Azure GPU build environments: provisioning, cost control, parity with the on-prem stack via pinned container/model versions; cloud-to-factory migration with parity regression
• GitOps CI/CD, container registry, artifact/model versioning, environment promotion; observability and audit wiring (Splunk, Prometheus/Grafana)
• Benchmark automation: load harness, p50/p95/p99 latency, tokens/sec, GPU utilization; the capacity report data pipeline
• Platform upgrade procedure with evaluation-regression gates; deployment runbook as a first-class deliverable

Technical Skills:

• 6+ years infrastructure/platform engineering with 3+ years production Kubernetes; OpenShift experience strongly preferred
• Hands-on GPU inference serving in production: NIM, Triton, vLLM, or TensorRT-LLM — you have sized, deployed, and tuned LLM serving on real GPUs and can talk memory-bandwidth trade-offs
• GitOps fluency (ArgoCD/Flux), infrastructure-as-code, container internals; comfortable in air-gapped/proxy-restricted enterprise networks
• Observability depth: metrics, traces, log pipelines; has built performance test harnesses, not just run them

• Azure or AWS GPU compute operations experience

Strongly preferred

• NVIDIA GPU operator and AI Enterprise stack specifics; KServe; Milvus or pgvector operations; VAST/NFS/S3 storage integration; banking or other regulated-environment delivery

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 NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

Job Description:

We are looking for a skilled Python Developer with 2+ years of hands-on experience in backend development and data processing. The ideal candidate should be proficient in Python and have working experience with web frameworks like Flask and FastAPI, along with exposure to data engineering and machine learning workflows.

Key Responsibilities:

Design, develop, and maintain scalable Python applications and APIs using Flask and FastAPI

Work with PySpark and Kafka for real-time data processing

Perform data manipulation and analysis using Pandas and NumPy

Develop and maintain modular, reusable, and testable code following OOP principles

Collaborate with data scientists to integrate ML models (TensorFlow, PyTorch, Scikit-learn) into production

Participate in code reviews, design discussions, and contribute to best practices

Write and maintain documentation for developed modules and workflows

Required Skills:

Strong proficiency in Python programming

Hands-on experience with Flask and/or FastAPI

Experience working with PySpark and Kafka

Solid understanding of Pandas, NumPy, and data handling in Python

Familiarity with TensorFlow, PyTorch, and scikit-learn

Good grasp of Object-Oriented Programming (OOP) concepts

Ability to write modular and maintainable code

Nice to Have:

Understanding of Machine Learning concepts and pipelines

Exposure to Generative AI (GenAI) technologies and tools

Experience with CI/CD tools, Docker, or cloud environments (AWS, GCP, etc.)

Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field

About the Role

We are looking for a dynamic and customer-focused Presales Engineer – Cloud & AI to support our Cloud Transformation, Modernization, Managed Services, and AI/GenAI practices.

This role is pivotal in shaping technical solutions for prospective customers, driving value-based conversations, and bridging the gap between customer challenges and Comprinno's cloud and AI capabilities.

As a Presales Engineer – Cloud & AI, you will work closely with Sales, Solution Architects, Data & AI teams, and Delivery teams to understand customer requirements, design high-level solutions, and articulate how Comprinno's offerings can accelerate digital transformation and business outcomes.

This is a high-impact role that combines cloud solutioning, technical consulting, AI awareness, customer engagement, and presales excellence.

Key Responsibilities

Customer Discovery & Solutioning

• Engage with prospective customers to understand business objectives, technical challenges, and transformation goals.
• Conduct discovery workshops, assessments, and technical discussions to identify cloud and AI opportunities.
• Translate business requirements into high-level cloud and AI solution architectures.
• Collaborate with Solution Architects and technical teams to develop scalable and cost-effective solutions.

Cloud Transformation Consulting

• Support customer initiatives across:
• Cloud Migration
• Application Modernization
• DevOps Transformation
• Managed Services
• Security & Compliance
• Resilience & Disaster Recovery
• Conduct cloud assessments and migration readiness evaluations.
• Prepare cloud cost estimates, modernization roadmaps, and optimization recommendations.
• Leverage AWS programs and frameworks such as:
• Migration Acceleration Program (MAP)
• AWS Well-Architected Framework (WAFR)
• Foundational Technical Review (FTR)

AI & GenAI Solution Consulting

• Identify opportunities for AI, GenAI, and Agentic AI adoption within customer environments.
• Participate in AI discovery workshops and business value discussions.
• Support solution design for AI-powered applications leveraging AWS AI services.
• Collaborate with Data & AI teams to position analytics, machine learning, and Generative AI offerings.
• Assist customers in identifying suitable use cases for:
• Generative AI
• AI Assistants
• Knowledge Management Solutions
• Intelligent Automation
• Conversational AI

Proposal Development & Technical Presales

• Collaborate with Solution Architects to create:
• Technical Proposals
• Architecture Diagrams
• Effort Estimates
• Statements of Work (SOWs)
• Technical Responses to RFPs/RFIs
• Present solutions, recommendations, and technical approaches to customer stakeholders.
• Support Proof of Concepts (PoCs), demonstrations, and technical validations.
• Participate in technical reviews and solution walkthroughs.

Customer Engagement & Thought Leadership

• Attend customer meetings jointly with Sales teams to provide technical expertise.
• Build credibility and trust with customer technical and business stakeholders.
• Contribute to webinars, workshops, technical presentations, and customer-facing events.
• Write blogs, case studies, solution briefs, and technical content that supports business growth.
• Maintain an active presence in cloud and AI communities.

Collaboration & Knowledge Management

• Collaborate with Delivery teams to ensure smooth handover and alignment between presales and execution.
• Maintain reusable presales assets, templates, assessment frameworks, and knowledge repositories.
• Continuously stay updated on AWS services, AI advancements, partner programs, and emerging technology trends.
• Contribute to internal capability building and knowledge-sharing initiatives.

Travel & Customer Interaction

• Travel as required for customer meetings, workshops, assessments, events, and strategic engagements.
• Represent Comprinno professionally during all customer-facing interactions.

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 3–5 years of experience in Presales, Solution Consulting, Cloud Consulting, Technical Sales, or related customer-facing roles.
• Strong understanding of AWS cloud services across:
• Compute
• Networking
• Storage
• Security
• Databases
• Knowledge of cloud migration and modernization frameworks such as AWS MAP.
• Familiarity with AWS cloud assessment tools including Migration Evaluator and AWS Well-Architected Tool.
• Understanding of:
• Kubernetes
• Containerization
• Cloud-Native Architectures
• DevOps Practices
• Hands-on exposure to Infrastructure as Code using Terraform or CloudFormation.
• Ability to create:
• Solution Documents
• Architecture Diagrams
• Technical Proposals
• Effort Estimates
• Statements of Work
• Understanding of Generative AI concepts including:
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Assistants
• Agentic AI Concepts
• Familiarity with AWS AI services such as:
• Amazon Bedrock
• Amazon SageMaker
• Amazon Q
• AWS Solutions Architect – Professional Certification.
• Experience positioning AI, GenAI, Analytics, or Data Engineering solutions.
• Familiarity with AI frameworks such as:
• LangChain
• LangGraph
• CrewAI
• OpenAI APIs
• Anthropic APIs
• Strong communication, presentation, and stakeholder management skills.
• Experience conducting AI assessments, GenAI workshops, or AI proof-of-concepts.
• Experience contributing to webinars, blogs, case studies, or technical marketing content.
• AWS Solutions Architect – Associate Certification (Mandatory).
• Customer-centric mindset with strong problem-solving abilities.

Desired Qualifications & Skills

• AWS Specialty Certifications such as:
• Security Specialty
• Advanced Networking Specialty
• Machine Learning Specialty
• DevOps Engineer Professional
• Understanding of compliance frameworks such as:
• ISO 27001
• SOC 2
• HIPAA
• MBA or equivalent business qualification.
• Contributions to industry blogs, webinars, conferences, technical communities, or open-source initiatives.

What We're Looking For

• Strong consulting mindset with the ability to understand customer business challenges.
• Excellent communication and presentation skills.
• Ability to balance technical depth with business value articulation.
• Passion for cloud technologies, AI, and emerging innovation.
• Collaborative team player who can work across Sales, Architecture, Delivery, and Product teams.
• High ownership and accountability.
• Curiosity and continuous learning mindset.
• Willingness to travel and work from customer locations across India and internationally as required by project engagements.

What Success Looks Like

• Consistently contributes to qualified pipeline creation and deal progression.
• Produces high-quality proposals, architecture recommendations, assessments, and Statements of Work.
• Builds credibility with customers through strong technical consulting and solution design.
• Successfully supports closure of Migration, Modernization, Managed Services, Security, and AI opportunities.
• Develops reusable presales assets, assessment frameworks, and solution accelerators.
• Contributes to thought leadership through blogs, webinars, technical presentations, and customer-facing content.
• Continuously expands expertise in AWS, Cloud, AI, and emerging technologies.

Why Join Comprinno

• Work at the forefront of Cloud, AI, and AWS innovation with one of the leading AWS Partners in APJ.
• Be part of real transformation initiatives involving Migration, Modernization, DevOps, Security, Managed Services, and Generative AI.
• Collaborate directly with enterprise customers and influence strategic technology decisions.
• Accelerate your growth through AWS certifications, mentorship, and hands-on customer engagements.
• Contribute to innovative solutions including Tevico and future AI-powered offerings.
• Build thought leadership through webinars, blogs, events, and community participation.
• Join a collaborative, high-performance culture that values ownership, innovation, and continuous learning.

Roles & Responsibilities

• Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.
• Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.
• Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.
• Should have knowledge of advanced prompting techniques.
• Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).
• Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.
• Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.
• Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.
• Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.
• Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks.
• Interact with cross-functional teams to understand system issues and follow up with respective teams to get them fixed.
• Understand and identify areas of improvement across businesses and participate in solution identification and implementation.
• Should be able to work as an Individual Contributor on new and existing projects.
• Positive and problem-solving attitude, must work as an independent contributor.

Ideal Candidate

1.Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

2.Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

3.Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support

4.Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

5.Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

6.Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models

.7.Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

8.Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

9.Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

10.Mandatory (CTC) - The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

11.Preferred (Experience 1) - Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and versioning of AI models.

12.Preferred (Experience 2) - Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.

13.Preferred (Experience 3) - Experience working with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.

14.Preferred (Experience 4) - Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architecture.

15.Preferred (Company) - Candidates from AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.

16.Mandatory ( Age ) - Candidate Should be Below 28 Years.

17.Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Location: Pune / Gurgaon

Position: AI Engineer

work mode: WFO

  Job Description.

​

 Job responsibilities:

• Responsibility for design, implementation and deployment of Generative AI, Agentic frameworks at scale
• Strong in programming - Python a
• Previous experience of working on Computer Vision projects and VLM /VLAM models.
• In depth awareness of Transformer architectures and End to End Deep neural networks
• Full stack AI / ML development experience
• Design, build & maintain efficient and reliable Agentic / Generative AI code leveraging pipelines
• Hosting and deployment knowledge in GCP or AWS or Azure along with advanced engineering concepts to build user friendly UI interface for easy adoption.

    Requirements:

 ·      4 to 8 years overall years of experience (Agentic AI, Generative AI, VLM, VLAM and LLM) with significant exposure in Development, Architecture design, scaling and hosting in cloud.

    Must Have –

 ·      Architecting and solutioning experience with Python and FAST API, Agentic Ai frameworks, VLMs, VLAMs, Open source LLM’s and Code based LLM models at scale with - Langchain /      Ollama, embeddings, Memory      Management etc.,

·      Practical experience in implementing Explainable and ethical AI models  Practical experience in implementing frameworks like RAG/ CAG/ Self-reflective RAG etc.,

·      Experience in cloud hosting either AWS or Azure or GCP.

·      Experience in ML-OPS - Implement a feedback mechanism to continually improve the model over time through feedback loop and monitoring KPI’s in production.

·      Experience with Quantization and Kubernetes or docker

    Good to have

·      gRPC implementation to expose the API’s on a server for easy usage and good user interface

·      Streamlit front end creation

·      Experience with SAFe framework deliveries.

Strong AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

3

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

4

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

5

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

6

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

7

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

8

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

9

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

10

Mandatory (Age) - Candidate's Age should be below 30 Years

11

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

12

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

13

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

14

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies

15

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

12

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13

Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14

Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15

Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

Strong AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

3

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

4

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

5

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

6

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

7

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

8

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

9

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

10

Mandatory (Age) - Candidate's Age should be below 30 Years

11

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

12

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

13

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

14

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies

15

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

12

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13

Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14

Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15

Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

12

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13

Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14

Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15

Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

About the Role :

As the Lead AI/ML Engineer, you will be responsible for leading the design, development, deployment, and continuous improvement of AI-powered solutions that create measurable impact in education. This role combines hands-on technical execution with engineering leadership, requiring you to architect scalable AI systems, mentor engineers, establish best practices, and collaborate closely with cross-functional teams to deliver production-grade solutions.

You will take ownership of the complete AI development lifecycle—from problem definition and data pipeline design to model training, deployment, monitoring, and optimization—while ensuring high standards of reliability, scalability, security, and performance. The role also involves evaluating emerging AI technologies and driving their adoption to enhance product capabilities and user experience.

Roles and Responsibilities:

• Lead the design, development, and deployment of AI-powered products for production environments.
• Drive technical architecture and decision-making across machine learning models, inference systems, cloud infrastructure, and distributed computing.
• Develop and maintain end-to-end machine learning pipelines, including data ingestion, model training, evaluation, deployment, monitoring, and continuous optimization.
• Design scalable, secure, and high-performance AI services capable of handling production-scale workloads.
• Provide technical leadership by mentoring engineers, conducting code and design reviews, and fostering engineering excellence.
• Establish and promote best practices for software quality, testing, performance optimization, observability, reliability, and maintainability.
• Collaborate closely with Product, Backend, Mobile, and Data teams to deliver robust, scalable, and business-focused AI solutions.
• Research, evaluate, and implement emerging AI technologies to enhance product capabilities and drive innovation.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
• Minimum 4 years of hands-on experience developing, deploying, and maintaining production-grade AI/ML systems.
• Strong proficiency in Python with excellent software engineering, object-oriented programming, and system design skills.
• Extensive experience with modern machine learning frameworks such as PyTorch, Hugging Face, TensorFlow, or equivalent.
• Proven expertise in deploying, optimizing, and scaling large language models (LLMs) and other AI models for production inference.
• Strong understanding of containerization and cloud-native technologies, including Docker, Kubernetes, AWS, and distributed system architectures.
• Demonstrated ability to lead technical initiatives, mentor engineering teams, and make sound architectural decisions.
• Excellent analytical, debugging, communication, and problem-solving skills.

Preferred Qualifications

• Hands-on experience with Large Language Models (LLMs), Computer Vision, Speech Recognition, Generative AI, or Multimodal AI systems.
• Experience with model optimization and inference technologies such as Quantization, Distributed Training, vLLM, TensorRT, ONNX Runtime, or similar frameworks.
• Prior experience developing AI solutions for the education, public sector, or other large-scale social impact initiatives.

Details:

• Location: Kothrud, Pune.
• Interested candidates should fill in the application on career website   https://careers.vopa.in/                                 
• Salary :- 12 LPA to 14 LPA (Depending on last drawn salary, Interview and Skills)

About Us

We are a fast-growing startup based in Pune, India, specializing in cutting-edge Data Science and Data Engineering solutions. Our team of dedicated professionals is committed to solving complex data challenges for companies worldwide.

Our Culture We foster a vibrant startup culture that values: • Intellectual curiosity • Continuous learning • Positive work environment • Collaborative problem-solving

Role Overview

We are seeking a versatile and proactive Data Scientist to join our dynamic team. The ideal candidate will possess a blend of technical expertise in modern AI/ML technologies, strategic planning, and effective communication skills. This role demands critical thinking, applying data science and problem-solving skills to a wide variety of real-world problems, adaptability to rapidly evolving technologies, and a strong foundation in both traditional and generative AI principles.

Key Responsibilities • Deliver end-to-end data science projects by applying Machine Learning and Deep Learning fundamentals to solve complex problems • Derive actionable insights for a variety of problems, industries, and domains using statistical analysis and advanced data science techniques • Develop high-quality software solutions with Python and other programming languages. Collaborate with developers to understand and improve existing code or create new solutions • Build and deploy production-ready LLM applications using modern frameworks and best practices • Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases and embedding models • Perform prompt engineering and optimization to maximize LLM performance for specific use cases • Implement agentic AI systems and multi-agent workflows for complex automation tasks • Evaluate and benchmark LLM outputs using appropriate metrics and testing frameworks • Build sophisticated data pipelines for large-scale data processing using modern orchestration tools • Optimize database performance and create efficient SQL queries • Deploy and monitor ML models in production using MLOps practices and containerization • Practice active listening to understand project requirements and team inputs • Collaborate with clients to translate business requirements into data science solutions • Communicate complex ideas and results clearly to stakeholders through both verbal and written formats • Apply responsible AI principles and ensure ethical considerations in model development • Demonstrate punctuality and a strong sense of ownership in all tasks • Plan strategically and multitask efficiently to meet project deadlines • Employ critical thinking to break down problems and debug effectively • Take initiative and be biased towards action to drive project progress Required Skills Core Programming & ML • Strong Python programming skills with hands-on project experience • Expertise in Machine Learning and Deep Learning algorithms (Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, Ensemble methods) • Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas • Familiarity with modern ML techniques: Transfer Learning, Few-shot Learning, Self-supervised Learning • Experience with NLP, Computer Vision, or Time Series Analysis Generative AI & LLMs • Hands-on experience with LLM providers (OpenAI, Anthropic Claude, Google Gemini, or open-source models) • Proficiency with GenAI orchestration frameworks (LangChain, LangGraph, LlamaIndex, or DSPy) • Experience building RAG applications with vector databases (Pinecone, Weaviate, Chroma, FAISS) • Strong prompt engineering skills and understanding of prompt optimization techniques • Knowledge of fine-tuning techniques (LoRA, QLoRA) and when to apply them • Understanding of LLM evaluation metrics and benchmarking methodologies • Familiarity with agentic AI architectures and multi-agent systems MLOps & Deployment • Experience with MLOps practices and tools (MLflow, Kubeflow, Weights & Biases) • Proficiency with containerization using Docker and orchestration with Kubernetes • Experience with cloud platforms (AWS, Azure, or GCP) for ML model deployment and monitoring • Understanding of CI/CD pipelines for ML applications • Knowledge of model serving frameworks and API development (FastAPI, Flask, or Django) Data Engineering & Databases • Solid understanding of SQL, including advanced concepts like windowing functions and query optimization • Experience with data pipeline orchestration tools (Airflow, Prefect, or similar) • Familiarity with both SQL and NoSQL databases Soft Skills & Professional Attributes • Strong critical thinking and problem-solving skills • Excellent written and verbal communication abilities • Demonstrated ability to work well in a team and independently • High degree of flexibility and adaptability to rapidly evolving technologies • Understanding of AI safety principles and responsible AI practices

Nice-to-Have • Experience with big data technologies (Spark, Hadoop, Databricks) • Familiarity with BI tools and dashboard creation (Tableau, Power BI, Looker) • Knowledge of graph databases and knowledge graph construction • Experience with real-time streaming data processing • Active participation in data science competitions (Kaggle, DrivenData) • Contributions to open-source AI/ML projects or technical blog • Experience with multimodal AI models (vision-language models, audio processing) • Published research papers or conference presentations

Qualifications • Data Scientist I: 0-2 years of hands-on experience in Data Science projects • Data Scientist II: 2-5 years of hands-on experience in Data Science projects • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field • Demonstrated commitment to continuous learning through courses, certifications, or self-study (especially in GenAI and modern ML techniques)

What We Offer • Competitive salary commensurate with experience • Opportunity to work on diverse, cutting-edge AI/ML projects • Collaborative and innovation-driven work environment • Rapid growth and continuous learning opportunities • Exposure to latest AI technologies and industry best practices

Link for application -  https://forms.gle/9GENVfPeXdtgi7Zj7

Job Description

Our Media Measurement team uses state-of-the-art technologies and rigorous methods to track who is watching what, where, and how they engage with content. Our clients can evaluate who is consuming which content across different media, platforms and devices, and know what the audience thinks about that content. As people consume media content on more channels, and through more devices, than ever before, we are proud to provide a full view on media consumption.

As Data Scientist you will have following main accountabilities: 

• You own together with your team several of our Data Science solutions throughout the full life cycle (brainstorming, design, implementation, productization and maintenance) 
• You develop solutions based on data science, stats and machine learning models 
• You improve methods and tools. Contribute to our communities of practice in the area of Data Science 
• Communicate with non-data scientists in Tech, Operations, Commercial, Product. Understand the domain and the requirements. Explain Data Science principles, concepts, algorithms, and approaches in simple words to different types of audiences 
• Make data your best friends. Understand their strengths and use them. Be aware of their weaknesses and handle those in your solutions 
• Screen the market for potential new Data Science approaches 
• Foster knowledge exchange within the company. Present GfK's Data Science expertise at conferences and workshops 

Qualifications

Now you know what a Data Scientist does. What skills, qualifications & experience do you need for this job? 

• You typically have a Master's degree or PhD that reflects modeling and statistics skills and 6+ years of experience. 
• You enjoy communicating complex methodology and technology to tech and non tech audiences 
• You have expert statistical / machine learning modeling skills (e.g. statistical tests, classification, predictive modelling, handling of missing data, sampling, weighting) 
• You have experience with an analytical programming language (Python) and the respective ecosystem 

Besides the things we really expect you to have, there are some things which would be amazing if you have experience with them: 

• Knowledge of cloud computing environments and tooling (especially AWS) 
• Advanced software development skills (unit testing, CI/CD, Git) 
• Basic skills regarding database handling as SQL 
• Basic knowledge of the always evolving Data Science ecosystem and its frameworks 

Additional Information

• Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms. 
• Recharge and revitalize with help of wellness plans made for you and your family. 
• Plan your future with financial wellness tools. 
• Stay relevant and upskill yourself with career development opportunities. 

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

Senior AI/ML Engineer

📍 Pune, Maharashtra (Onsite)

💼 Experience: 6–10 Years

🕒 Employment Type: Full-Time

About the Role

We are seeking a highly skilled Senior AI/ML Engineer to lead the design, development, and deployment of enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will possess strong expertise in production-grade Retrieval-Augmented Generation (RAG) systems, deep learning architectures, semantic search platforms, vector databases, and AI orchestration frameworks.

This role requires hands-on technical leadership, architectural ownership, and proven experience building scalable AI systems that operate reliably in production environments.

Key Responsibilities

• Design and architect enterprise-grade RAG (Retrieval-Augmented Generation) solutions
• Build and optimize document chunking, retrieval, reranking, and hallucination mitigation pipelines
• Develop and deploy machine learning models using XGBoost, PyTorch, and TensorFlow
• Design deep learning solutions including LSTM and transformer-based architectures
• Build semantic search and vector retrieval systems using modern vector databases
• Develop advanced AI workflows using LangChain and LangGraph
• Design and implement multi-agent AI systems and orchestration frameworks
• Lead AI model deployment, monitoring, optimization, and lifecycle management
• Collaborate with cross-functional teams to translate business requirements into scalable AI solutions
• Mentor junior engineers and contribute to technical leadership initiatives
• Drive AI architecture decisions, performance tuning, and best practices

Required Skills & Qualifications

Must-Have Technical Skills

• 6–10 years of software engineering and AI/ML development experience
• Strong experience building and deploying production AI/ML systems
• Hands-on expertise with RAG architectures and semantic retrieval systems
• Experience with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Qdrant
• Strong knowledge of Machine Learning and Deep Learning concepts
• Hands-on experience with:
• PyTorch and/or TensorFlow
• XGBoost
• LangChain
• LangGraph
• Experience deploying AI applications in production environments
• Strong debugging, performance optimization, and troubleshooting skills
• Excellent Python programming skills
• Understanding of REST APIs, microservices, and scalable system design

Preferred Skills

• MLflow
• Weights & Biases (W&B)
• Kubeflow
• Transformer architectures and LLM internals
• MLOps practices and model lifecycle management
• Multi-agent AI frameworks
• Cloud platforms such as AWS, Azure, or GCP
• Docker and Kubernetes
• CI/CD pipelines for AI applications

Ideal Candidate Profile

You are someone who:

• Has successfully deployed AI solutions into production environments
• Understands enterprise-scale AI architecture and design patterns
• Has practical experience with retrieval systems and vector search
• Can independently drive AI initiatives from concept to deployment
• Enjoys solving complex engineering challenges
• Demonstrates strong ownership, leadership, and mentoring capabilities
• Thrives in a fast-paced product and engineering environment

Who Should Not Apply

• Prompt-engineering-only profiles
• Candidates with only academic or research exposure
• Tutorial/demo-level GenAI practitioners
• Engineers without production deployment experience
• Professionals lacking hands-on implementation expertise

Educational Qualification

• B.E. / B.Tech in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, or related discipline
• Master's degree is a plus

Work Location

📍 Pune, Maharashtra (Onsite)

Hiring Preference

• Immediate joiners preferred
• Candidates currently working on production AI/ML systems will be given preference

Keywords

AI Engineer, Senior AI Engineer, Machine Learning Engineer, Generative AI Engineer, LLM Engineer, RAG Engineer, LangChain, LangGraph, Vector Database, Semantic Search, Deep Learning, PyTorch, TensorFlow, XGBoost, ML Engineer, AI Architect, MLOps, Multi-Agent Systems, Production AI

Role & Responsibilities

Responsibilities

• Contribute to the development and optimization of enterprise-wide search systems and models.

• Design and implement algorithms to improve indexing, query relevance, and search accuracy.

• Support taxonomy, ontology, and metadata model creation for better search outcomes.

• Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.

• Conduct analysis of user behavior and system metrics to refine search performance.

• Work with engineers, product managers, and designers to deliver integrated search solutions.

• Develop production-grade ML systems for ranking, personalization, and recommendations.

• Participate in proof-of-concept initiatives with internal and external partners.

• Follow best practices in software engineering including CI/CD, testing, and monitoring.

• Keep abreast of emerging developments in AI/ML to apply them in practical solutions.

Ideal Candidate

Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

Mandatory (Age) - Candidate's Age should be below 30 Years

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.

Kindly provide the following details while sending your CV: (Mandatory details)

1) Date of Birth

2) Current Location-

3) Current CTC-

4) Expected CTC-

5) Notice Period-

6) Ready to relocate to Pune?

Regards,

The Supreme Consultancy

Website- https://lnkd.in/eawfxfxU

Job Overview:

We are looking for a high-ownership Software Engineer with hands-on experience in modern full-stack development. The role demands strong fundamentals, the ability to work in a startup environment, and a mindset to build, iterate, and scale products.

You will be working closely with founders and cross-functional teams to build robust, scalable, and high-performance applications.

Core Responsibilities

·        Develop and maintain web applications using Next.js (frontend) and Nest.js (backend)

·        Design, build, and optimize RESTful APIs and backend services

·        Translate business requirements into scalable technical solutions

·        Collaborate with product, design, and business teams for feature development

·        Debug, troubleshoot, and improve application performance

·        Ensure code quality through clean architecture, testing, and best practices

·        Participate in deployment, monitoring, and continuous improvement cycles 

Technical Requirements

·        Strong proficiency in JavaScript and TypeScript

·        Solid understanding of web fundamentals (HTML, CSS, APIs, browser behavior)

·        Hands-on experience with Next.js and Nest.js

·        Working knowledge of PostgreSQL or relational databases

·        Familiarity with Git and GitHub (version control workflows)

·        Understanding of API design principles and backend architecture

Good-to-Have Skills

·        Experience with deployment platforms (Digital Ocean, AWS, Docker, etc.)

·        Knowledge of authentication, authorization, and security practices

·        Exposure to CI/CD pipelines

·        Understanding of scalable system design basics

What We Want

·        Strong problem-solving mindset

·        Ability to learn fast and adapt quickly

·        Comfort working in an unstructured startup environment

·        Ownership-driven attitude (not just task execution)

·        Clear communication and collaboration skills

Ideal Candidate Profile

·        Projects demonstrating end-to-end ownership

·        Contributions on GitHub (active repositories, clean code)

·        Experience building real-world applications (not just tutorials)

·        Ability to explain technical decisions and trade-offs

What You Will Get

·        Opportunity to work directly with startup founders

·        Fast-paced learning environment and accelerated skill development

·        Exposure to real product building and scaling challenges

·        Freedom to experiment, build, and innovate

·        Performance-driven growth and responsibility

·        Competitive compensation aligned with your potential

Additional Details

·        Joining: Immediate (7–15 days preferred)

·        Probation: 3 Months 

JOB DETAILS:

- Job Title: Lead I - Data Science - Python, Machine Learning, Spark 

- Industry: Global Digital Transformation Solutions Provider

- Experience: 5-10 years

- Job Location: Pune

- CTC Range: Best in Industry

JD for Data Scientist

Hands-on experience with data analysis tools:

Proficient in using tools such as Python and R for data manipulation, querying, and analysis.

Skilled in utilizing libraries like Pandas, NumPy, and Scikit-Learn to perform in-depth data analysis and modeling.

Skilled in machine learning and predictive analytics:

Expertise in building, training, and deploying machine learning models using frameworks such as TensorFlow and PyTorch.

Capable of performing tasks like regression, classification, clustering, and recommendation, leading to data-driven predictions and insights.

Expertise in big data technologies:

Proficient in handling large datasets using big data tools such as Spark.

Skilled in employing distributed computing and parallel processing techniques to ensure efficient data processing, storage, and analysis, enabling enterprise-level solutions and informed decision-making

Skills: Python, SQL, Machine Learning, and Deep Learning, with mandatory expertise in Generative AI.

Must-Haves

5–9 years of relevant experience in Python, SQL, Machine Learning, and Deep Learning, with mandatory expertise in Generative AI

******

NP - Immediate joiners only

Location-Pune 

Generative AI System Design

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

2️⃣ Backend & Microservices Engineering

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

3️⃣ Cloud-Native Architecture & DevOps

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

Experience: Experience: 10+ years of experience in software development & project management, with specialization in AI/ML

Qualification: B.E/B.Tech

Location: Pune

Role Overview

We are seeking a Head of AI Center of Excellence to execute our enterprise AI strategy. This role will be responsible for designing and delivering agentic AI systems and production-grade AI solutions, while driving rapid experimentation and pilot-ready proof-of-concepts in a fast-paced environment.

·    Required Qualifications:

• 10+ years of overall software development & management experience with 5+ years of hands-on experience in AI/ML system design and development
• Experience with technical project management; managing a team of AI/ML engineers across multiple projects
• Proven expertise in:
• Agentic AI architectures, LLM-based systems, and orchestration frameworks
• ML/DL model development, training, fine-tuning, and evaluation
• MLOps, model deployment, monitoring, and lifecycle management
• Strong proficiency in Python and modern AI/ML frameworks (e.g., LangGraph, PyTorch, TensorFlow, Hugging Face)
• Experience with cloud platforms and AI services (AWS, Azure, or GCP)
• Demonstrated ability to deliver pilot-ready AI PoCs quickly and effectively

Description

We are currently hiring for the position of Data Scientist/ Senior Machine Learning Engineer (6–7 years’ experience).

Please find the detailed Job Description attached for your reference. We are looking for candidates with strong experience in:

• Machine Learning model development
• Scalable data pipeline development (ETL/ELT)
• Python and SQL
• Cloud platforms such as Azure/AWS/Databricks
• ML deployment environments (SageMaker, Azure ML, etc.)

Kindly note:

• Location: Pune (Work From Office)
• Immediate joiners preferred

While sharing profiles, please ensure the following details are included:

• Current CTC
• Expected CTC
• Notice Period
• Current Location
• Confirmation on Pune WFO comfort

Must have skills

Machine Learning - 6 years

Python - 6 years

ETL(Extract, Transform, Load) - 6 years

SQL - 6 years

Azure - 6 years

Data Scientist or Senior Machine Learning Engineer

We are currently hiring for the position of Data Scientist/ Senior Machine Learning Engineer (6–7 years' experience).

Please find the detailed Job Description attached for your reference.

We are looking for candidates with strong experience in:

• Machine Learning model development
• Scalable data pipeline development (ETL/ELT)
• Python and SQL
• Cloud platforms such as Azure/AWS/Databricks
• ML deployment environments (SageMaker, Azure ML, etc.)

Kindly note:

• Location: Pune (Work from Office)
• Immediate joiners preferred

While sharing profiles, please ensure the following details are included:

• Current CTC
• Expected CTC
• Notice Period
• Current Location
• Confirmation on Pune WFO comfort

Must have Skills

• Machine Learning - 6 Years
• Python - 6 Years
• ETL (Extract, Transform, Load) - 6 Years
• SQL - 6 Years
• Azure - 6 Years

Request you to share relevant profiles at the earliest. Looking forward to your support.

Job Title : QA Lead (AI/ML Products)

Employment Type : Full Time

Experience : 4 to 8 Years

Location : On-site

Mandatory Skills : Strong hands-on experience in testing AI/ML (LLM, RAG) applications with deep expertise in API testing, SQL/NoSQL database validation, and advanced backend functional testing.

Role Overview :

We are looking for an experienced QA Lead who can own end-to-end quality for AI-influenced products and backend-heavy systems. This role requires strong expertise in advanced functional testing, API validation, database verification, and AI model behavior testing in non-deterministic environments.

Key Responsibilities :

• Define and implement comprehensive test strategies aligned with business and regulatory goals.
• Validate AI/ML and LLM-driven applications, including RAG pipelines, hallucination checks, prompt injection scenarios, and model response validation.
• Perform deep API testing using Postman/cURL and validate JSON/XML payloads.
• Execute complex SQL queries (MySQL/PostgreSQL) and work with MongoDB for backend and data integrity validation.
• Analyze server logs and transactional flows to debug issues and ensure system reliability.
• Conduct risk analysis and report key QA metrics such as defect leakage and release readiness.
• Establish and refine QA processes, templates, standards, and agile testing practices.
• Identify performance bottlenecks and basic security vulnerabilities (e.g., IDOR, data exposure).
• Collaborate closely with developers, product managers, and domain experts to translate business requirements into testable scenarios.
• Own feature quality independently from conception to release.

Required Skills & Experience :

• 4+ years of hands-on experience in software testing and QA.
• Strong understanding of testing AI/ML products, LLM validation, and non-deterministic behavior testing.
• Expertise in API Testing, server log analysis, and backend validation.
• Proficiency in SQL (MySQL/PostgreSQL) and MongoDB.
• Deep knowledge of SDLC and Bug Life Cycle.
• Strong problem-solving ability and structured approach to ambiguous scenarios.
• Awareness of performance testing and basic security testing practices.
• Excellent communication skills to articulate defects and QA strategies.

What We’re Looking For :

A proactive QA professional who can go beyond UI testing, understands backend systems deeply, and can confidently test modern AI-driven applications while driving quality standards across the team.

Core Responsibilities:

• The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and efficiency
• Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.
• Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.
• Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.
• System Integration: Integrate models into existing systems and workflows.
• Model Deployment: Deploy models to production environments and monitor performance.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders.
• Continuous Improvement: Identify areas for improvement in model performance and systems.

Skills:

• Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).
• Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch, Neo4J graph
• Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.
• Knowledge of model monitoring and performance evaluation.

Required experience:

• Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sagemaker pipeline with ability to analyze gaps and recommend/implement improvements
• AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in ML workflows
• AWS data: Redshift, Glue
• Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)

Skills: Aws, Aws Cloud, Amazon Redshift, Eks

Must-Haves

Amazon SageMaker, AWS Cloud Infrastructure (S3, EC2, Lambda), Docker and Kubernetes (EKS, ECS), SQL, AWS data (Redshift, Glue)

Skills : Machine Learning, MLOps, AWS Cloud, Redshift OR Glue, Kubernetes, Sage maker

******

Notice period - 0 to 15 days only 

Location : Pune & Hyderabad only

We are looking for a Senior AI / ML Engineer to join our fast-growing team and help build AI-driven data platforms and intelligent solutions. If you are passionate about AI, data engineering, and building real-world GenAI systems, this role is for you!

🔧 Key Responsibilities

• Develop and deploy AI/ML models for real-world applications

• Build scalable pipelines for data processing, training, and evaluation

• Work on LLMs, RAG, embeddings, and agent workflows

• Collaborate with data engineers, product teams, and software developers

• Write clean, efficient Python code and ensure high-quality engineering practices

• Handle model monitoring, performance tuning, and documentation

Required Skills

• 2–5 years of experience in AI/ML engineering

• Strong knowledge of Python, TensorFlow/PyTorch

• Experience with LLMs, GenAI, RAG, or NLP

• Knowledge of Databricks, MLOps or cloud platforms (AWS/Azure/GCP)

• Good understanding of APIs, distributed systems, and data pipelines

🎯 Good to Have

• Experience in healthcare, SaaS, or big data

• Exposure to Databricks Mosaic AI

• Experience building AI agents

MUST-HAVES: 

• Machine Learning + Aws + (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) + Sage maker
• Notice period - 0 to 15 days only 
• Hybrid work mode- 3 days office, 2 days at home

SKILLS: AWS, AWS CLOUD, AMAZON REDSHIFT, EKS

ADDITIONAL GUIDELINES:

• Interview process: - 2 Technical round + 1 Client round
• 3 days in office, Hybrid model. 

CORE RESPONSIBILITIES:

• The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and efficiency
• Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.
• Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.
• Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.
• System Integration: Integrate models into existing systems and workflows.
• Model Deployment: Deploy models to production environments and monitor performance.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders.
• Continuous Improvement: Identify areas for improvement in model performance and systems.

SKILLS:

• Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).
• Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaos search logs, etc. for troubleshooting; Other tech touch points are Scylla DB (like BigTable), OpenSearch, Neo4J graph
• Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.
• Knowledge of model monitoring and performance evaluation.

REQUIRED EXPERIENCE:

• Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sage maker pipeline with ability to analyze gaps and recommend/implement improvements
• AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in ML workflows
• AWS data: Redshift, Glue
• Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)

Job Details

- Job Title: ML Engineer II - Aws, Aws Cloud

- Industry: Technology

- Domain - Information technology (IT)

- Experience Required: 6-12 years

- Employment Type: Full Time

- Job Location: Pune

- CTC Range: Best in Industry

Job Description:

Core Responsibilities:

? The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and efficiency

? Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.

? Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.

? Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.

? System Integration: Integrate models into existing systems and workflows.

? Model Deployment: Deploy models to production environments and monitor performance.

? Collaboration: Work closely with data scientists, software engineers, and other stakeholders.

? Continuous Improvement: Identify areas for improvement in model performance and systems.

Skills:

? Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).

? Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch, Neo4J graph

? Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.

? Knowledge of model monitoring and performance evaluation.

Required experience:

? Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sagemaker pipeline with ability to analyze gaps and recommend/implement improvements

? AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in

ML workflows

? AWS data: Redshift, Glue

? Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)

Skills: Aws, Aws Cloud, Amazon Redshift, Eks

Must-Haves

Aws, Aws Cloud, Amazon Redshift, Eks

NP: Immediate – 30 Days

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

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).

Role Overview

We're looking for a highly motivated AI Intern to join our dynamic team. This isn't your average internship; you'll be diving headfirst into the exciting world of Natural Language Processing (NLP) and Large Language Models (LLMs). You will work on real-world projects, contributing directly to our core products by researching, developing, and fine-tuning state-of-the-art language models. If you're passionate about making machines understand and generate human language, this is the perfect role for you!

Skills Needed:

1. Python
2. ML
3. NLP
4. LLM Fine-Tuning
5. Fast API

What You'll Do (Key Responsibilities)

Develop & Implement LLM Models: Assist in building and deploying LLM solutions for tasks like sentiment analysis, text summarization, named entity recognition (NER), and question-answering.

Fine-Tune LLMs: Work hands-on with pre-trained Large Language Models (like Llama, GPT, BERT) and fine-tune them on our custom datasets to enhance performance for specific tasks.

Data Pipeline Management: Be responsible for data preprocessing, cleaning, and augmentation to create high-quality datasets for training and evaluation.

Experiment & Evaluate: Research and experiment with different model architectures and fine-tuning strategies (e.g., LoRA, QLoRA) to optimize for accuracy, speed, and cost.

Collaborate & Document: Work closely with our senior ML engineers and data scientists, actively participating in code reviews and clearly documenting your findings and methodologies.

Must-Have Skills (Qualifications)

Strong Python Proficiency: You live and breathe Python and are comfortable with its data science ecosystem (Pandas, NumPy, Scikit-learn).

Solid ML & NLP Fundamentals: A strong theoretical understanding of machine learning algorithms, deep learning concepts, and core NLP techniques (e.g., tokenization, embeddings, attention mechanisms).

Deep Learning Frameworks: Hands-on experience with either PyTorch or TensorFlow.

Familiarity with LLMs: You understand the basics of transformer architecture and have some exposure to working with or fine-tuning Large Language Models.

Problem-Solving Mindset: An analytical and curious approach to tackling complex challenges.

Educational Background: Currently pursuing or recently graduated with a degree in Computer Science, AI, Data Science, or a related technical field.

Brownie Points For (Preferred Skills)

Experience with the Hugging Face ecosystem (Transformers, Datasets, Tokenizers).

A portfolio of personal or academic projects on GitHub showcasing your AI/ML skills.

Familiarity with vector databases (e.g., Pinecone, ChromaDB).

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:

Responsibilities

● Design, build, and deploy applied ML models (NLP, LLM-based) to solve real-world sales tech problems.

● Build and orchestrate true multi-agent systems to collaboratively solve complex tasks and workflows that reason, remember, plan, and take actions over structured and unstructured data.

● Use frameworks like LangGraph, CrewAI, or custom planners to orchestrate LLM-powered agents.

● Prototype and productionize capabilities using foundation models (OpenAI, Claude, Gemini, etc.), embeddings, and vector databases (e.g., Pinecone, Weaviate).

● Work with the product team to integrate intelligent agents into customer CRM workflows and GTM-facing tools.

● Design observability, evaluation and control mechanisms to ensure agent reliability, traceability, safety and frugality.

● Continuously improve agents with RF and active learning.

Requirements

● Bachelor’s or Master’s in Computer Science, AI/ML, or a related field.

● 2+ years of experience deploying ML models or AI systems in production

environments.

● Experience with LLMs, NLP pipelines, prompt engineering, and fine-tuning.

● Familiarity with agentic frameworks (LangChain, LangGraph, AutoGPT, CrewAI, or custom orchestration).

● Strong Python programming skills and deep knowledge of the ML/LLM ecosystem.

● Hands-on experience with MLOps, API integrations, and cloud infrastructure (AWS, GCP, or Azure).

● Ability to balance rapid experimentation with robust engineering.

Nice to Have

● Experience working with sales/revenue data (CRM, Gong, Salesforce, LinkedIn).

● Familiarity with reasoning techniques (ReAct, CoT, Tree-of-Thoughts), graph orchestration, and tool chaining.

● Exposure to multi-agent systems, RAG pipelines, or feedback loops in production.

● Contributions to open-source AI/agentic tools or frameworks.

Job Title : AI Architect

Location : Pune (On-site | 3 Days WFO)

Experience : 6+ Years

Shift : US or flexible shifts

Job Summary :

We are looking for an experienced AI Architect to design and deploy AI/ML solutions that align with business goals.

The role involves leading end-to-end architecture, model development, deployment, and integration using modern AI/ML tools and cloud platforms (AWS/Azure/GCP).

Key Responsibilities :

• Define AI strategy and identify business use cases
• Design scalable AI/ML architectures
• Collaborate on data preparation, model development & deployment
• Ensure data quality, governance, and ethical AI practices
• Integrate AI into existing systems and monitor performance

Must-Have Skills :

• Machine Learning, Deep Learning, NLP, Computer Vision
• Data Engineering, Model Deployment (CI/CD, MLOps)
• Python Programming, Cloud (AWS/Azure/GCP)
• Distributed Systems, Data Governance
• Strong communication & stakeholder collaboration

Good to Have :

• AI certifications (Azure/GCP/AWS)
• Experience in big data and analytics

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.

We are seeking a highly skilled Senior/Lead Data Scientist with deep expertise in AI/ML/Gen AI, including Deep Learning, Computer Vision, and NLP. The ideal candidate will bring strong hands-on experience, particularly in building, fine-tuning, and deploying models, and will work directly with customers with minimal supervision.

This role requires someone who can not only lead and execute technical projects but also actively contribute to business development through customer interaction, proposal building, and RFP responses. You will be expected to take ownership of AI project execution and team leadership, while helping Tekdi expand its AI footprint.

Key Responsibilities:

Contribute to AI business growth by working on RFPs, proposals, and solutioning activities.

• Lead the team in delivering customer requirements, ensuring quality and timely execution.

Develop and fine tune advanced AI/ML models using deep learning and generative AI techniques.

• Fine-tune and optimize Large Language Models (LLMs) such as GPT, BERT, T5, and LLaMA.
• Interact directly with customers to understand their business needs and provide AI-driven solutions.
• Work with Deep Learning architectures including CNNs, RNNs, and Transformer-based models.
• Leverage NLP techniques such as summarization, NER, sentiment analysis, and embeddings.
• Implement MLOps pipelines and deploy scalable AI solutions in cloud environments (AWS, GCP, Azure).
• Collaborate with cross-functional teams to integrate AI into business applications.
• Stay updated with AI/ML research and integrate new techniques into projects.

Required Skills & Qualifications:

• Minimum 6 years of experience in AI/ML/Gen AI, with at least 3+ years in Deep Learning/Computer Vision.
• Strong proficiency in Python and popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, Scikit-learn).
• Hands-on experience with LLMs and generative models (e.g., GPT, Stable Diffusion).
• Experience with data preprocessing, feature engineering, and performance evaluation.
• Exposure to containerization and cloud deployment using Docker, Kubernetes.
• Experience with vector databases and RAG-based architectures.
• Ability to lead teams and projects, and work independently with minimal guidance.
• Experience with customer-facing roles, proposals, and solutioning.

Educational Requirements:

• Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Information Technology, or related field.

Preferred Skills (Good to Have):

• Knowledge of Reinforcement Learning (e.g., RLHF), multi-modal AI, or time-series forecasting.
• Familiarity with Graph Neural Networks (GNNs).
• Exposure to Responsible AI (RAI), AI Ethics, or AutoML platforms.
• Contributions to open-source AI projects or publications in peer-reviewed journals.

• Strong AI/ML OR Software Developer Profile
• Mandatory (Experience 1) - Must have 3+ YOE in Core Software Developement (SDLC)
• Mandatory (Experience 2) - Must have 2+ years of experience in AI/ML, preferably in conversational AI domain (spped to text, text to speech, speech emotional recognition) or agentic AI systems.
• Mandatory (Experience 3) - Must have hands-on experience in fine-tuning LLMs/SLM, model optimization (quantization, distillation) and RAG
• Mandatory (Experience 4) - Hands-on Programming experience in Python, TensorFlow, PyTorch and model APIs (Hugging Face, LangChain, OpenAI, etc

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

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.)

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.

About the company

KPMG International Limited, commonly known as KPMG, is one of the largest professional services networks in the world, recognized as one of the "Big Four" accounting firms alongside Deloitte, PricewaterhouseCoopers (PwC), and Ernst & Young (EY). KPMG provides a comprehensive range of professional services primarily focused on three core areas: Audit and Assurance, Tax Services, and Advisory Services. Their Audit and Assurance services include financial statement audits, regulatory audits, and other assurance services. The Tax Services cover various aspects such as corporate tax, indirect tax, international tax, and transfer pricing. Meanwhile, their Advisory Services encompass management consulting, risk consulting, deal advisory, and other related services.

Apply through this link for quicker response-https://forms.gle/aSyXcxVNzQptbWt9A

Job Description

Position: ML Engineer

Experience: Experience 4+ years of relevant experience

Location :  WFO (3 days working) Pune – Kharadi

Employment Type:  contract for 3-5 months-Can be extended basis performance and future requirements

Skills Required:

  • Building and maintaining pipelines for model development, testing, deployment, and monitoring. 

• Automating repetitive tasks such as model re-training, hyperparameter tuning, and data validation. 

• Developing CI/CD pipelines for seamless code migration. 

• Collaborating with cross-functional teams to ensure proper integration of models into production systems. 

Key Skills 

• 3+ years of experience in developing and deploying ML models in production. 

• Strong programming skills in Python (with familiarity in Bash/Shell scripting). 

• Hands-on experience with tools like Docker, Kubernetes, MLflow, or Airflow. 

• Knowledge of cloud services such as AWS SageMaker or equivalent. 

• Familiarity with DevOps principles and tools like Jenkins, Git, or Terraform. 

• Understanding of versioning systems for data, models, and code. 

• Solid understanding of MLflow, ML services, model monitoring, and enabling logging services for performance tracking

Key Responsibilities:

• Develop and maintain scalable Python applications for AI/ML projects.
• Design, train, and evaluate machine learning models for classification, regression, NLP, computer vision, or recommendation systems.
• Collaborate with data scientists, ML engineers, and software developers to integrate models into production systems.
• Optimize model performance and ensure low-latency inference in real-time environments.
• Work with large datasets to perform data cleaning, feature engineering, and data transformation.
• Stay current with new developments in machine learning frameworks and Python libraries.
• Write clean, testable, and efficient code following best practices.
• Develop RESTful APIs and deploy ML models via cloud or container-based solutions (e.g., AWS, Docker, Kubernetes).

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