Senior Machine Learning Engineer specializing in RL and locomotion to develop and deploy policies for legged robotic platforms, owning the full pipeline from simulation training to real-world deployment.
Responsibilities
- Develop and implement reinforcement learning based locomotion policies for legged robots using GPU-accelerated simulation environments such as Isaac Gym and Isaac Lab.
- Create terrain curricula and domain randomization to improve policy robustness under real-world conditions.
- Manage the sim-to-real transfer pipeline, analyze reality gaps, and implement solutions to close them.
- Train locomotion policies for stair climbing, rough-terrain traversal, payload carriage, push recovery, and fall recovery scenarios.
- Define and assess metrics that quantify locomotion performance and robustness.
- Collaborate with manipulation and perception teams to integrate locomotion into the full autonomy stack.
Requirements
- Three or more years of experience applying reinforcement learning to legged or mobile robotics (3-8+ years).
- Strong foundation in dynamics, control, and robot locomotion.
- Experience with RL algorithms such as PPO and SAC, and training frameworks including rsl_rl, Stable Baselines, and rl_games.
- Hands-on experience with physics simulation tools like Isaac Gym, MuJoCo, and PyBullet.
- Proven track record of sim-to-real transfer on physical robotic systems.
- Proficiency in Python and PyTorch.
- Eligibility to obtain and maintain a U.S. security clearance.
Technologies
- Isaac Gym
- Isaac Lab
- MuJoCo
- PyBullet
- Python
- PyTorch
- PPO
- SAC
- rsl_rl
- Stable Baselines
- rl_games
- NVIDIA Isaac Lab
- Omniverse
Benefits
- Equity grants
- Comprehensive benefits package for full-time employees
About the team
The Frontier Systems group at Anduril is developing the next generation of robotic platforms for defense and industrial applications. We are a compact, high-performing team of roboticists, ML engineers, and systems engineers delivering real-world capability to operators in the field. Our platforms operate in unstructured, contested environments where robustness and reliability are non-negotiable.
About the job
We are seeking a Senior Machine Learning Engineer who specializes in RL and locomotion to design and deploy locomotion policies for legged robotic platforms. You will own the full pipeline from simulation training to real-world deployment, building systems that enable robust mobility across challenging terrain such as rubble, stairs, slopes, and degraded environments. Your work will determine whether our platforms can operate where warfighters rely on them.
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