Design, develop, and deploy production-grade generative AI and machine learning solutions. Build LLM applications, RAG and GraphRAG systems, intelligent agents, chatbots, search and recommendation systems, and scalable AI pipelines. Fine-tune models, optimize prompts, work with structured and unstructured data, and deliver reliable API-based AI services. Collaborate with product, engineering, and business teams to translate requirements into practical AI applications and evaluate emerging AI technologies.
This role is for one of Weekday’s clients
Salary range: Rs 3000000 - Rs 5000000 (ie INR 30 - 50 LPA)
Min Experience: 5+ years
Location: Mumbai, Maharashtra, India
JobType: full-time
We are looking for a Senior Data Scientist with strong expertise in Generative AI, Large Language Models (LLMs), and Machine Learning to design, develop, and deploy production-grade AI solutions. The ideal candidate will have hands-on experience building LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, GraphRAG architectures, and intelligent AI agents. This role involves developing scalable AI applications, fine-tuning models, and translating complex business requirements into practical AI-driven solutions.
RequirementsKey Responsibilities
- Design, build, and deploy production-ready Artificial Intelligence and Machine Learning solutions.
- Develop and optimize LLM-powered applications using RAG, GraphRAG, Agentic AI, and multimodal AI technologies.
- Fine-tune and customize Large Language Models using LoRA, PEFT, transfer learning, and other relevant techniques.
- Build intelligent chatbots, search engines, recommendation systems, and knowledge retrieval applications.
- Design and optimize prompt engineering frameworks for business-specific use cases.
- Develop scalable AI pipelines, model-serving frameworks, and API-based AI services.
- Work with structured and unstructured datasets to build predictive and generative AI solutions.
- Collaborate with Product, Engineering, and Business teams to translate business challenges into AI-driven applications.
- Evaluate emerging AI models, technologies, frameworks, and tools, recommending their adoption where relevant.
- Ensure deployed AI solutions are scalable, reliable, secure, and production-ready.
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- GraphRAG
- Prompt Engineering
- AI Agents and Agentic Workflows
- LLM Fine-Tuning using LoRA and PEFT
- Embeddings and Vector Search
- Multimodal AI Applications
- Strong programming skills in Python.
- Hands-on experience with LangChain and LangGraph.
- Experience with Neo4j and graph databases.
- Familiarity with vector databases such as Pinecone, ChromaDB, Weaviate, PgVector, or equivalent technologies.
- Strong understanding of classification and regression models.
- Ability to apply Machine Learning concepts to predictive and generative AI use cases.
- Experience working with structured and unstructured data.
- Generative AI
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Model Context Protocol (MCP)
- Google Agent Development Kit (ADK)
- Experience with AutoGen, CrewAI, or Semantic Kernel.
- Knowledge of multi-agent architectures and advanced Agentic AI workflows.
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