Generative AI Engineer

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

Skills Required
Docker, Cuda, FastAPI, Azure, Aws, Python