About The Role

You will build AI that survives contact with real users — which mostly means retrieval that finds the right thing, evaluation that catches regressions, and knowing when the honest answer is that a language model is the wrong tool. We ship RAG assistants, agents and document intelligence into production, with citations and refusal behaviour rather than demos.

What you’ll do

- Build production RAG and agent systems on Azure OpenAI, Anthropic and open models
- Own retrieval quality end to end: chunking, ranking, grounding and citation correctness
- Build the evaluation suites — a fixed question set with known-valuable answers, scored on every change
- Design guardrails against prompt injection, data leakage and confidently wrong answers
- Instrument cost and latency per request, and make the trade-offs visible to the client
- Say plainly when a problem is better solved with a query, a rule or a classifier than with an LLM

What we’re looking for




- Three or more years in ML or software engineering, with production LLM systems you can describe in detail
- Strong Python, and comfort with the async and streaming shape of LLM applications
- Practical grasp of embeddings, vector search and where retrieval actually breaks
- You have run an evaluation and changed your mind because of it

Nice to have Not required. Apply if the section above fits.
- Fine-tuning or preference tuning in production
- Document intelligence over messy PDFs and scans
- MLOps: model versioning, drift monitoring, feature stores

How to apply Send your CV to [email protected] with “AI / ML Engineer” in the subject line, or WhatsApp it to +91 95605 15123. Either reaches the same team, and we reply to every application.

Email your CV Send on WhatsApp

📌 AI / ML Engineer (Noida)
🏢 ITLabz Technology
📍 Noida