Staff AI Engineer, Robot Learning (Navigation)
- Full-time
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we’re growing the team to take it even further.
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-gen robot learning systems for humanoid navigation, behavior 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.
What You'll Do
Develop next-generation learned navigation systems that integrate complex spatial reasoning and semantic goals to drive robust, real-world robot behaviors.
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 behaviors 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 productionize 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 behavior-learning roadmap.
What We’re Looking For
Extensive experience in machine learning for embodied AI, with a proven track record explicitly focused on end-to-end (e2e) learned behaviors 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 behavior‑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.
What We Offer
Competitive equity: stock options with meaningful upside as we scale.
30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).
Private healthcare, including virtual and in‑person care.
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
Free daily breakfast, catered lunch, and snacks in‑office.
Work at the frontier - collaborate daily with world‑class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
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