ML Engineer

Requirements:

• 3-5 years of experience in software engineering, AI/ML engineering, or applied ML.
• Strong Python programming and software engineering fundamentals.
• Hands-on experience building and deploying LLM, GenAI, NLP, or AI/ML applications.
• Practical experience with RAG, retrieval, embeddings, search, or context selection.
• Backend development, API design, testing, debugging, and system design.
• Understanding of AI evaluation, quality measurement, and regression testing.
• Production deployment experience with Docker and AWS or equivalent cloud platforms.
• Ability to optimise latency, cost, reliability, and system performance.

Good-to-Have Skills:

• Vector databases: Qdrant, pgvector, or similar.
• Graph databases, Neo4j, knowledge graphs, or graph-based retrieval.
• LangChain, LlamaIndex, or similar LLM orchestration frameworks.
• Redis, PostgreSQL, S3, queues, background jobs, and asynchronous processing.
• Hugging Face, vLLM, model serving, fine-tuning, or model optimisation.
• Recommendation systems, ranking, user modelling, or personalisation.
• Langfuse, tracing, observability, and AI evaluation tools.
• Multilingual NLP, Indic languages, or domain-specific knowledge systems.