ML Research Engineer - Member of Technical Staff
On-siteLondon, England, United Kingdom
Job Summary
Design and run experiments isolating failures in agentic systems across behavior, traces, and activations to drive improvements in intelligence, cost, and reliability. Attack core research themes including context and memory management, agent steering, task decomposition, continual learning, and inter-agent communication. Build durable agent analysis and evaluation infrastructure for observability, behavior analysis, and auditing that the entire company relies on. Publish evaluation results, methods, and discoveries as both company assets and public evidence. Work across team boundaries to design systems running at unprecedented scale at lowest cost and latency, or invent novel architectures exploiting emerging unconventional silicon. This role shapes the science behind application-aware orchestration across heterogeneous models and hardware for the General Capabilities Team.
Required Qualifications
- Evidence that you can run research of your own
- Deep hands-on experience with LLMs in agentic settings
- Real experimental discipline
- Strong engineering
- Strong communication skills
Desired Qualifications
- Evaluations, benchmarks or agent harnesses you built that other people went on to use
- Experience with RL or post-training for long-horizon, multi-step or tool-use tasks
- Depth in multi-agent systems, planning, program synthesis, or retrieval over structured artefacts such as codebases
- Deep familiarity with the internals of SGLang, vLLM, or comparable inference serving frameworks
- A background in another field that studies systems of interacting heterogeneous components
- A published track record in a relevant field
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