About the role
Requirements:
- Core Python Mastery: 8+ years of production experience writing clean, scalable, and maintainable Python (asyncio, design patterns, testing, performance profiling).
- LLM and Generative AI: Experience working with frameworks like LangChain, LlamaIndex, AutoGen, or Hugging Face Transformers, alongside commercial APIs (OpenAI, Anthropic).
- Vector Databases: Hands-on experience with vector search engines like Pinecone, Milvus, Qdrant, Chroma, or pgvector.
- Machine Learning Fundamentals: Strong knowledge of PyTorch or TensorFlow, scikit-learn, Pandas, NumPy, and model evaluation techniques.
- Cloud and Infrastructure: Proven experience deploying containerised AI workloads (Docker, Kubernetes) on cloud platforms (AWS, GCP, or Azure).
- Data and API Architecture: Experience with PostgreSQL, Redis, Kafka/RabbitMQ, and REST/gRPC interfaces.
Good-to-Have:
- Experience with LLM evaluation frameworks (Ragas, TruLens, Arize).
- Experience with local model serving frameworks (vLLM, Ollama, TGI).
- B. S. or M. S. in Computer Science, Data Science, Artificial Intelligence, or a related field.
Tech Stack:
- Primary Language: Python.
- AI/ML: PyTorch, Hugging Face, LangChain, LlamaIndex, vLLM.
- Databases: PostgreSQL, Redis, Qdrant / Pinecone.
- Frameworks: FastAPI, Flask, Celery.
- DevOps/MLOps: Docker, Kubernetes, MLflow, AWS/GCP.