Data Scientist

We are looking for an experienced Data Science Team Lead with a strong hands-on background in Machine Learning, Deep Learning, Generative AI, Transformers, and production AI solutions. The candidate should have strong theoretical knowledge along with practical experience in designing, developing, deploying, and optimizing AI systems.

Key Responsibilities

• Lead, mentor, and technically guide a team of Data Scientists, ML Engineers, and AI Engineers.
• Design and develop production-grade ML, DL, and Generative AI solutions.
• Work extensively with Transformers, LLMs, Embeddings, RAG, AI Agents, Multi-Agent Systems, MCP, and Multimodal AI (text/image).
• Design and implement end-to-end RAG pipelines including document processing, chunking, embeddings, vector search, hybrid retrieval, reranking, context construction, and generation.
• Develop agentic workflows using tool calling, function calling, MCP, LangChain, LangGraph, CrewAI, and related frameworks.
• Work with both open-source and commercial LLMs, including OpenAI, Gemini, and other third-party providers.
• Deploy and optimize open-source LLMs using vLLM, llama.cpp, Ollama, Hugging Face Transformers, and other inference frameworks.
• Perform LLM fine-tuning using techniques such as SFT, LoRA, QLoRA, and PEFT.
• Build systematic LLM evaluation and observability pipelines to measure quality, hallucination, groundedness, retrieval performance, latency, cost, and reliability.
• Work with PyTorch for model development, training, fine-tuning, and optimization.
• Apply Machine Learning, Deep Learning, Time Series, and statistical modeling techniques to real-world business problems.
• Work with GPU/CUDA infrastructure, optimize model memory and inference performance, and support scalable AI deployments.
• Conduct research on emerging AI technologies, evaluate their business value, and rapidly adapt to new technology requirements.
• Design AI-powered workflow automation using technologies such as Playwright and external APIs.
• Collaborate with engineering, product, business, and client teams to translate business requirements into scalable AI solutions.

Required Skills & Experience

• 5+ years of professional experience in Data Science, Machine Learning, AI, or a related field.
• Strong theoretical and practical understanding of ML, DL, Transformers, and Generative AI.
• Strong hands-on experience with Python and PyTorch.
• Experience building and deploying production AI/ML/GenAI solutions.
• Strong experience with RAG, AI Agents, Multi-Agent Systems, MCP, Embeddings, and LLM applications.
• Experience with LLM fine-tuning and open-source LLM inference.
• Experience with Vector Databases such as Qdrant, Milvus, Pinecone, Weaviate, or Elasticsearch/OpenSearch.
• Working knowledge of CUDA, GPU infrastructure, model optimization, and inference performance.
• Experience with cloud AI/ML platforms such as AWS SageMaker, AWS Bedrock, Azure ML, or equivalent services.
• Experience with LangChain, LangGraph, CrewAI, Hugging Face Transformers, or similar frameworks.
• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders and clients.
• Proven ability to lead teams, mentor engineers, conduct research, and drive technical decisions.

Preferred Domain Experience

• Experience in Healthcare, Insurance, ERP, Enterprise Automation, or Document Processing will be highly valuable.