Senior Machine Learning Research Engineer

Skills

About the Role

You will develop learning-based algorithms for dynamic locomotion and whole-body control. You will build reusable motion capabilities, train and evaluate policies in simulation and on physical robots, optimize real-time performance, and integrate learned behaviors into the robot control and autonomy stack.

Requirements

• BS, MS, or PhD in Robotics, Machine Learning, Computer Science, or a related technical field
• 3+ years of experience developing machine learning systems in industry or research
• Understanding of deep learning and modern policy architectures
• Experience with reinforcement learning and an additional learning area such as imitation learning or generative models
• Python and PyTorch experience
• Experience with physics-based simulation environments such as Isaac Lab, Isaac Sim, or MuJoCo
• Ability to apply learning algorithms to dynamics, control, and physical systems

Responsibilities

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

Benefits

• Stock options
• 30+ paid days off including annual leave, UK bank holidays, and company closure days
• Private healthcare
• Pension scheme with 8% total contribution
• Free daily breakfast, catered lunch, and in-office snacks