AI / ML Engineer

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-good 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.