Machine Learning Engineer- Reinforcement Learning

Machine Learning Engineer- Reinforcement Learning focuses on inspect, maintain, repair, install, design, or improve technical systems according to the role.

What the role involves

• Inspect, maintain, repair, install, design, or improve technical systems according to the role.
• Diagnose issues, complete checks, and keep records or handovers accurate.

Skills and requirements

• 3-5 years training and deploying deep RL agents in Python.
• PyTorch or JAX, and RL libraries such as Gymnasium.
• Comfortable iterating between research exploration and the engineering needed to run on a live site.
• A degree in engineering, CS, or physics.

Confirmed role details

• ML Engineer - Reinforcement Learning London (hybrid, 1 day/week in Kings Cross)- Solve Data Centres Cooling issues.
• Design reward functions and constraints that hold up against physical limits and SLAs, not just in a notebook.
• Move between research-style exploration and the engineering work to make something stable on a real site.
• Build and improve the physics-based simulators, surrogate models, and digital twins the agents train against.

Candidate fit

• £110K-£150K, plus competitive equity.
• A genuine technical problem: RL on physical systems, under real constraints, deployed on live infrastructure.
• Hybrid working, one day a week in the Kings Cross office.

Additional role context

• Reward and constraint design is shaped by ASHRAE standards and customer SLAs - air temperature, humidity, and rate-of-change limits on cooling air and chilled water setpoints.