AI Engineer, Robot Learning; Navigation

About The Role

We're hiring a Staff AI Engineer, Robot Learning (Navigation) to join our Perception and Navigation team based in London. In this role you will lead the design, development, and optimisation of next‑generation robot learning systems for humanoid navigation, behaviour learning, multi‑agent interaction, and semantic goal reasoning in dynamic environments. We are interested in candidates who have a track record of driving end‑to‑end learned behaviours into production (e.g. self‑driving, drones, robot navigation and other autonomous systems).

At the Staff level, you aren’t just implementing existing models; you are defining the paradigm for how humanoids interact with a dynamic, unpredictable world. You will own the stack that transitions our robots from structured laboratory tasks to fluid, real‑world autonomy.

• Develop next‑generation learned navigation systems that integrate complex spatial reasoning and semantic goals to drive robust, real‑world robot behaviours.
• Work on open‑ended navigation powered by Vision‑Language‑Action (VLA) models, enabling robots to understand context, navigate multi‑agent environments, predict intent, and act safely in dynamic spaces.
• Design and scale data pipelines and evaluation frameworks optimized for training large‑scale, end‑to‑end (e2e) learned behaviours and multimodal navigation models.
• Architect and deploy highly reliable ML systems, taking models out of simulation/labs and hardening them for predictable, repeatable execution on physical hardware.
• Collaborate with cross‑functional research and engineering teams to product ionise large vision‑language‑action models, ensuring production metrics meet strict real‑world reliability standards.
• Stay ahead of the field, rapidly evaluate new model architectures, multi‑agent strategies, and datasets to guide our embodied AI and behaviour‑learning roadmap.

• Extensive experience in machine learning for embodied AI, with a proven track record explicitly focused on end‑to‑end (e2e) learned behaviours using large models (VLAs, VLMs, transformers, or diffusion).
• Deep production expertise: you are someone who gets things into production that work reliably. You have hands‑on experience deploying, monitoring, and optimizing large‑scale ML systems.
• Strong background in spatial reasoning and semantic goals, with experience handling multi‑agent dynamics, crowding, or interactive environments.
• Proficiency in PyTorch and the modern tooling required to train, fine‑tune, and deploy large‑scale foundation models for robotics.
• Exceptional experimental and engineering skills, capable of taking ambitious behaviour‑learning concepts from initial research to rock‑solid deployment on physical robots.
• Comfortable working in a fast‑moving, research‑driven environment with evolving models, data, and tools.

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), separate sick leave, and paid bank holidays and company holidays.
• Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.
• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.
• Free daily breakfast, catered lunch, and snacks in‑office.
• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
• Freedom to influence the product and own key initiatives.