Data Scientist
key Responsibilities:
- Fine-tune and adapt open-source LLMs (e.g., LLaMA 4, Mistral and Bert) using NVIDIA GPU tools.
- Build AI agents using frameworks like LangChain, LangGraph, or AutoGen with structured workflows (memory, tools, retries, etc.).
- Implement hybrid LLM solutions using OpenAI/Claude APIs and open-source models.
- Develop APIs using FastAPI and containerize apps with Docker.
- Deploy, monitor, and scale AI solutions on AWS, Azure, or similar cloud providers.
- Collaborate with senior engineers to optimize performance and reliability of deployed systems.
Requirements:
- Hands-on experience with LLM fine-tuning and NVIDIA GPU toolkits (CUDA).
- Familiarity with LangChain or similar agent frameworks.
- Experience developing APIs with FastAPI and deploying via Docker.
- Proficiency in using OpenAI/Anthropic APIs and building basic RAG pipelines.
- Solid foundation in Python, cloud deployment (AWS/Azure), and vector databases (e.g., FAISS, Pinecone).
Nice to have:
- Exposure to tools like LangServe and Semantic Kernel
- Familiarity with CI/CD pipelines and monitoring tools (e.g., GitHub Actions, Prometheus).
- Contribution to open-source AI/ML projects.
Soft Skills:
Strong communication skills - both verbal and written
Excellent problem-solving and debugging skills
Self-motivated with the ability to work independently and in a team
Comfortable working with stakeholders across different time zones
