Robot Learning Engineer (AI/Robotics)

Location: London, UK (King’s Cross), on-site five days a week. Visa sponsorship and relocation to London are available.

Company

hirify.global develops commercially scalable and safe hirify.global robots; its HMND-01 platform is deployed in real industrial environments.

What you will do

• Post-train manipulation policies with behaviour cloning and reinforcement learning, owning the loop from raw data through deployment on real robots.
• Set up reinforcement learning on a digital twin, iterate on reward design and simulation quality, and improve sim-to-real transfer.
• Define data quality, diversity, coverage, and operator instructions with the Data Collection organization; design preprocessing strategies to improve collected data.
• Expand observation and action spaces for new capabilities and work with Teleoperations to expose them to robot operators.
• Improve motion smoothness and the teleoperation experience with Controls teams.
• Feed hardware limitations into future hardware design and make pre-training research advances reliable in industrial demonstrations.

Requirements

• 3+ years working on robots in industry or research, with shipped work and a demonstrable track record.
• Hands-on experience with modern manipulation methods, ideally close to production deployment.
• Solid understanding of modern teleoperation and low-level robot control stacks.
• Experience applying neural-network post-training, including behaviour cloning and reinforcement learning, to physical systems.
• Familiarity with deep-learning infrastructure, including streaming datasets, checkpointing, distributed training, PyTorch or JAX, and profiling and debugging numerical issues.
• Strong software engineering and coding fundamentals, including maintainable research code, clear experiment documentation, and concise communication of trade-offs.
• Ability to debug physical robot failures, drive open-ended problems proactively, and prioritize making systems work on robots over perfect simulation algorithms.
• Working English.

Nice to have

• Experience training VLA models for manipulation, including autoregressive, diffusion, or flow-matching approaches; familiarity with OpenVLA and Physical Intelligence models.
• Experience applying reinforcement learning to robotic problems.
• PhD or postdoctoral experience from a top robotics or machine-learning program.
• Publications at top-tier robotics or deep-learning conferences, or equivalent open-source contributions.
• Strong PhD students close to finishing and postdocs are welcome even if slightly below the experience bar.

Culture & Benefits

• Senior or staff individual-contributor role with no management track and direct impact on real robots.
• Access to prototype hardware and direct input on product direction and key initiatives.
• Stock options with meaningful upside as the company scales.
• More than 30 paid days off, including 23 days of annual leave, UK bank holidays, and a company shutdown between Christmas and New Year.
• Fully funded private healthcare with virtual and in-person care and mental-health support.
• 8% total pension contribution, free breakfast, catered lunch, and office snacks.

Hiring process

• Introductory call with hirehire’s AI researcher, followed by an HR screen with hirify.global.
• LeetCode-style coding round and robot-learning specialization interview.
• Technical execution interview focused on working, collaborating, and driving problems, with an optional conversation with a tech leader.