Staff AI Engineer: Robotics Navigation & Learning

Humanoid; Greater London; On-site; GBP 110,000 - 170,000; Full time

Benefits offered by this job

Equity

Paid leave

Private healthcare

Pension scheme

On-site meals

Job summary

Humanoid in London is hiring a Staff AI Engineer, Robot Learning (Navigation) to lead the design, development, and optimization of learned navigation for humanoid robots. You will own the stack from research to production, enabling real-world autonomy with safe, reliable systems.

The role focuses on end-to-end learned behaviors, large scale models, and production pipelines, collaborating across research and engineering to push the frontier of embodied AI.

Qualifications

• Extensive experience in ML for embodied AI with end-to-end learned behaviors.
• Hands-on track record deploying, monitoring and optimizing large-scale ML systems.
• Strong spatial reasoning and semantic goal handling in dynamic environments.

Responsibilities

• Develop next-generation navigations systems with spatial reasoning and semantic goals.
• Work on Vision-Language-Action models for context understanding and safe navigation.
• Design and scale data pipelines and evaluation frameworks for end-to-end learned behaviors.
• Architect and deploy reliable ML systems on real robots, beyond simulation.
• Collaborate with researchers and engineers to productionize large models.
• Stay ahead of the field by evaluating new architectures and datasets.

Skills

End-to-end ML systems

Embodied AI

VLAs / VLMs / transformers

PyTorch

Production deployment

Spatial reasoning

Tools

PyTorch

Job description

Humanoid in London is hiring a Staff AI Engineer, Robot Learning (Navigation) to lead the design, development, and optimization of learned navigation for humanoid robots. You will own the stack from research to production, enabling real-world autonomy with safe, reliable systems.

The role focuses on end-to-end learned behaviors, large scale models, and production pipelines, collaborating across research and engineering to push the frontier of embodied AI.