Machine Learning Engineer

Responsibilities

• Build the robot-learning stack from the ground up, including training infrastructure, data pipelines, and simulation environments
• Stand up ML infrastructure for training pipelines, experiment tracking, and data versioning
• Train policies across manipulation, locomotion, and whole-body control coupling
• Deploy policies through a phased rollout strategy to build production trust
• Collaborate with mechanical, perception, and robotics engineers

Requirements

• Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related field
• 2+ years of hands-on robot learning experience with real hardware deployment
• Experience with sim-to-real transfer and domain randomization
• Implementation experience with diffusion-based or flow-matching action policies
• Reinforcement learning experience applied on real hardware
• Strong programming skills in Python and PyTorch
• Practical experience with NVIDIA Isaac Sim, Isaac Lab, or MuJoCo
• Comfort with debugging and iterating on physical robots

Preferred Qualifications

• Edge inference experience (TensorRT, ONNX, quantization)
• Visual self-supervised representation learning experience
• Legged-robot or whole-body control experience
• Physics-informed ML experience
• Experience building ML pipelines in a team setting

Benefits

• Daily free lunch
• Flexible PTO
• Comprehensive medical, dental, and vision coverage
• Paid parental leave
• 401(k) retirement plan
• Employee referral bonuses

About the Company

Path Robotics is building the future of embodied intelligence, creating AI-driven systems that enable robots to adapt and perform in the real world to transform industries.