RL Research Engineer — Grounded, Multi‑Step Bio Lab

Dex; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Dex is partnering with a frontier RL lab in London to hire an early Member of Technical Staff in Reinforcement Learning. You will own the full research loop, from designing environments and reward functions to scaling distributed training on large GPU clusters.

You will work directly with domain scientists to translate biological questions into verifiable tasks and shape the tech stack and engineering standards as a foundational hire.

Qualifications

• Deep, first-principles understanding of reinforcement learning, with demonstrated experience debugging exploration, credit assignment, and reward hacking in large-scale models or complex agents.
• Strong research engineering instincts, capable of writing performant code and debugging everything from learning dynamics down to distributed systems and GPU performance.
• Hands-on experience building agentic systems, custom RL environments, tool-use architectures, or training setups for multi-step, long-horizon tasks.
• Based in or willing to relocate to London, working on-site five days a week in the lab.

Responsibilities

• Build grounded RL environments, reward structures, and evaluation frameworks that force genuine scientific reasoning and actively resist reward hacking.
• Train agents on multi-step reasoning, tool use, and long-horizon exploration across complex biological datasets.
• Architect and scale the rollout, distributed training, and evaluation infrastructure required to run high-throughput experiments on large GPU clusters.
• Partner directly with domain scientists to convert ambiguous biological questions into formal environments with verifiable outcomes.
• Shape the technical stack, research discipline, and engineering standards as one of the lab's foundational hires.

Skills

Reinforcement learning

Research engineering

Distributed systems

GPU performance

Agentic systems

Job description

Dex is partnering with a frontier RL lab in London to hire an early Member of Technical Staff in Reinforcement Learning. You will own the full research loop, from designing environments and reward functions to scaling distributed training on large GPU clusters.

You will work directly with domain scientists to translate biological questions into verifiable tasks and shape the tech stack and engineering standards as a foundational hire.