Machine Learning Research Engineer (Robotics)

Location: London, UK; on-site

Company

hirify.global develops commercially scalable and safe hirify.global robots, including the HMND-01 platform for real industrial environments.

What you will do

• Design and train learning-based locomotion and whole-body control policies for dynamic hirify.global robot behaviors.
• Develop reusable motion primitives using reinforcement learning, imitation learning, generative models, and other learning-based approaches.
• Build simulation, data generation, and training pipelines with platforms such as Isaac Lab and MuJoCo.
• Develop robustness, adaptation, domain randomization, and sim-to-real transfer methods using simulated and real-world robot data.
• Deploy, evaluate, debug, and fine-tune learned policies on physical hirify.global robots.
• Integrate and optimize learned policies within the real-time robot control and autonomy stack.

Requirements

• BS, MS, or PhD in Robotics, Machine Learning, Computer Science, or a related technical field.
• At least 3 years of experience developing machine learning systems in industry or research.
• Strong understanding of deep learning and modern policy architectures, including training, inference, experimentation, and debugging.
• Hands-on experience with reinforcement learning and at least one additional area such as imitation learning, generative models, sequence models, or large-scale representation learning.
• Strong Python and PyTorch experience.
• Experience with physics-based simulation environments such as Isaac Lab, Isaac Sim, MuJoCo, or similar platforms, and the ability to reason about learning algorithms in the context of dynamics and control.

Nice to have

• Experience applying reinforcement learning or imitation learning to legged robots, hirify.globals, or other complex physical systems.
• Experience with whole-body control, locomotion, motion imitation, loco-manipulation, or deployment on real robotic systems.
• Familiarity with motion capture, trajectory optimization, model-based control, or learning from demonstrations.
• Experience training policies at scale across large numbers of simulated environments.
• Publications at NeurIPS, ICML, ICLR, CoRL, RSS, CVPR, or equivalent open-source robotics or machine learning contributions.

Culture & Benefits

• Competitive equity through stock options.
• More than 30 paid days off, including annual leave, UK bank holidays, and company closure days.
• Private healthcare with virtual and in-person care.
• Pension scheme with an 8% total contribution.
• Daily breakfast, catered lunch, and snacks in the office.
• Daily collaboration with engineers, researchers, and product experts building hirify.global robotics and AI systems, with direct access to founding leadership.