DeepMind is hiring a Staff Staff LLM Engineer — RAG & agents on the Applied LLM team (Hybrid · London, United Kingdom). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.
You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
DeepMind builds frontier AI for science and products used by Google and partners worldwide. Our London teams work on large-scale training, alignment, and safe deployment of language and multimodal systems.
We are hiring a Staff LLM Engineer (hybrid, London) to lead retrieval-augmented and agentic systems for research tooling and internal products—with rigorous evals and reproducible releases.
What you will do
- Ship production LLM and retrieval systems with clear evaluation, monitoring, and rollback paths—not demo-only notebooks.
- Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout.
- Improve data quality, labeling, and offline metrics that correlate with business KPIs.
- Document architectures and runbooks for on-call and customer-facing teams.
- Mentor engineers on testing, observability, and responsible AI practices.
What we look for
- Strong Python and modern ML/LLM stack experience with multiple shipped features.
- Comfort with SQL, experimentation, and communicating results to non-technical stakeholders.
- Pragmatic ownership from prototype to production—including cost and latency budgets.
- Eligible to work in the listed country; professional English (French a plus for Paris roles).