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Senior Data Scientist
4 weeks ago
Role Overview:
We are seeking a highly skilled Senior Data Scientist with hands-on experience in Generative AI to design, build, and deploy advanced AI solutions. This role involves working on cutting-edge projects like RAG-based chatbots, LLM-driven BI systems, and autonomous coding agents. You will collaborate cross-functionally with engineering teams to turn AI prototypes into scalable production systems.
Key Responsibilities:
- Architect and implement end-to-end Generative AI solutions (e.g., RAG chatbots, AI-powered BI tools, code-generating agents)
- Develop intelligent agents using LangGraph or similar orchestration frameworks
- Build scalable data ingestion and retrieval pipelines leveraging LlamaIndex and related libraries
- Design and maintain high-performance vector databases for semantic search and information retrieval
- Integrate and benchmark multiple LLM providers (OpenAI, Gemini, Claude, etc.)
- Set up monitoring and observability systems using tools like LangSmith for real-time tracking of AI performance
- Work closely with engineering teams to productionize machine learning models and applications
Required Skills & Qualifications:
3–7 years total experience, with a minimum of 1 year focused on Generative AI
Generative AI Expertise:
- Practical experience with LangGraph or equivalent frameworks for agent orchestration
- Strong knowledge of LlamaIndex , LangChain , or similar libraries for document processing
- Proficiency with vector databases (Pinecone, Chroma, Weaviate, etc.)
- Familiarity with LLM APIs from providers like OpenAI , Anthropic , and Google
- Hands-on experience with LLM observability tools such as LangSmith, Weights & Biases
- Demonstrated ability to build natural language to SQL BI tools
- Proven experience in building RAG systems for contextual chatbot solutions
- Experience in developing code generation agents and LLM-based programming assistants
Traditional AI & Machine Learning:
- Solid foundation in ML techniques such as classification, regression, clustering, and time-series forecasting
- Proficiency with frameworks like scikit-learn , TensorFlow , and PyTorch
- Experience in statistical analysis , A/B testing , and experimental design
- Strong data handling skills, including feature engineering and preprocessing
