Data Scientist, ML / GenAI / LLM

What you'll do

• Design and implement advanced machine learning solutions to solve complex business problems.
• Build, train, and optimize ML models using both structured and unstructured data.
• Develop Generative AI applications including conversational AI, summarization, and information extraction.
• Implement Retrieval-Augmented Generation (RAG) solutions using enterprise data sources.
• Build robust data and ML pipelines for model training, inference, and production deployment.
• Apply MLOps principles to ensure AI applications are scalable, reliable, and production-ready.
• Implement LLM evaluation and monitoring approaches to ensure accuracy and performance.
• Develop solutions using Python and frameworks like PyTorch, TensorFlow, or Hugging Face.

What we're looking for

• Must have 10+ years of experience.
• Strong hands-on experience in Data Science and Machine Learning.
• Strong programming skills in Python.
• Experience developing and productionizing ML models and ML pipelines.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with prompt engineering, RAG, embeddings, vector search/vector databases, and LLM evaluation.
• Experience with ML/AI frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or similar technologies.
• Working knowledge of MLOps, model deployment, monitoring, versioning, and CI/CD concepts.
• Experience with cloud-based data and AI platforms such as AWS, Azure, or GCP.
• Experience with LLM orchestration/frameworks such as LangChain, LlamaIndex, or similar tools (preferred).
• Knowledge of AI agents / Agentic AI and tool-calling architectures (preferred).
• Familiarity with LLM guardrails, responsible AI, security, and governance considerations (preferred).
• Experience optimizing GenAI solutions for latency, scalability, reliability, and cost (preferred).