Senior Deep Learning Engineer for Whole-Body Control

Humanoid; United Kingdom; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Stock options

Paid time off

Private healthcare

Pension plan

Free daily meals

Frontier work environment

Access to leadership

Job summary

Humanoid in the United Kingdom seeks a Deep Learning Engineer to advance learning-based locomotion and whole-body control on its humanoid platform. You will build robust motion primitives and work with robotics, controls, simulation and ML engineers to run learned policies in real-time.

You’ll deploy and refine policies on physical humanoid robots, optimize latency, and contribute to sim-to-real transfer while collaborating with a world‑class team and access to equity and strong welfare

Qualifications

• BS, MS, or PhD in Robotics, ML, CS, or related field.
• 3+ years of industry/research ML system experience.
• Strong deep learning understanding and policy architectures.
• Hands-on RL and at least one additional area (imitation, generative, seq models).
• Strong Python and PyTorch experience.
• Experience with physics-based simulation environments (Isaac Lab/Sim, MuJoCo).
• Ability to reason about learning algorithms in dynamics and control.

Responsibilities

• Design and train locomotion and whole-body control policies for dynamic robotic behaviors.
• Develop motion primitives using learning-based generative models.
• Apply RL, imitation learning and other learning approaches to motion generation and control.
• Build scalable simulation, data generation, and training pipelines (Isaac Lab, MuJoCo).
• Develop methods for robustness, sim-to-real transfer, domain randomization.
• Deploy, evaluate, debug, and fine-tune learned policies on real humanoid robots.
• Optimize policy inference and training for real-time control latency.
• Integrate learned policies into the robot control and autonomy stack.

Skills

Python

PyTorch

Reinforcement learning

Imitation learning

Motion control

Education

BS, MS, or PhD in Robotics

Tools

Isaac Lab

Isaac Sim

MuJoCo

Job description

Humanoid in the United Kingdom seeks a Deep Learning Engineer to advance learning-based locomotion and whole-body control on its humanoid platform. You will build robust motion primitives and work with robotics, controls, simulation and ML engineers to run learned policies in real-time.

You’ll deploy and refine policies on physical humanoid robots, optimize latency, and contribute to sim-to-real transfer while collaborating with a world‑class team and access to equity and strong welfare