Reinforcement Learning Engineer (Robotics)

TL;DR

Reinforcement Learning Engineer (Robotics): Building high-performance, robust manipulation policies for hirify.global robots across simulation and physical environments with an accent on language-vision conditioning, real-world training pipelines, and sim-to-real transfer. Focus on designing challenging manipulation tasks, collecting trajectories for behavior cloning, and solving the engineering challenges of deploying deep RL policies on physical robots.

Location: On-site in London, UK

Company

Develops commercially scalable and safe hirify.global robots, including a platform already operating in real industrial pilots.

What you will do

• Train language-vision conditioned manipulation policies with reinforcement learning in simulation and the real world.
• Build diverse and challenging manipulation task suites in robotics simulators.
• Collect simulation trajectories with teleoperations for behavior cloning.
• Establish real-world reinforcement learning training pipelines with testing and operations teams.
• Experiment with methods for transferring policies from simulation to physical robots.

Requirements

• 3+ years of experience building deep-learning systems in industry or research, with shipped models or published artifacts.
• Hands-on experience with LLMs, VLMs, or image/video generative models, including architecture, training, and inference.
• Experience solving real-world problems with reinforcement learning and deep neural networks.
• Strong Python and PyTorch or JAX skills, including profiling, numerical debugging, and maintainable research code.
• Self-directed approach, proactive communication, clear experiment documentation, and concise communication of trade-offs.

Nice to have

• Experience with robotics simulators such as Isaac Sim or MuJoCo.
• Experience applying reinforcement learning to robotics.
• Experience building large-scale RL infrastructure with tools such as Ray.
• Publications at ICLR, ICML, NeurIPS, or equivalent open-source contributions.
• Familiarity with OpenVLA, Physical Intelligence models, or similar open VLA frameworks.

Culture & Benefits

• Competitive equity through stock options.
• 30+ paid days off, including annual leave, UK bank holidays, and company closure days.
• Private healthcare with virtual and in-person care.
• Pension scheme with an 8% total contribution.
• Daily breakfast, catered lunch, and snacks in the office.
• Work alongside engineers, researchers, and product experts on AI and hirify.global robotics at the frontier of the field.