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Machine Learning Engineer, Robot Learning, Loco-Manipulation

1 week, 6 days ago
United States
Full-time
Junior
Machine Learning Engineer
Software Development
Python PyTorch Reinforcement Learning
Apply Now
Path Robotics

Path Robotics

Path Robotics creates truly autonomous robots for manufacturing, eliminating the need for skilled welders or robot programmers and allowing humans to focus on creativity.

Automotive
51-250
Founded 2014
$71M raised
View All Jobs 37

Description

  • Build the robot-learning stack from the ground up, including training infrastructure, data pipelines, simulation environments, model architectures, and deployment workflows.
  • Stand up machine learning infrastructure such as training pipelines, experiment tracking, data versioning, and reproducible sim-to-real workflows.
  • Train policies for manipulation, locomotion, and whole-body control across cobots, industrial arms, and mobile platforms.
  • Develop and fine-tune action generation approaches using behavioral cloning, diffusion models, flow-matching, and reinforcement learning.
  • Deploy models in phased production rollouts and use real-world execution data to continuously improve performance.
  • Collaborate daily with mechanical engineers, perception engineers, robotics engineers, and manufacturing domain experts.
  • Participate in within-department rotation across home teams as needed.

Requirements

  • Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field, or equivalent experience.
  • 2+ years of hands-on robot learning experience with policies trained and deployed on real robot hardware.
  • Experience with sim-to-real transfer, including simulation environments, domain randomization, and debugging policy transfer failures.
  • Implementation experience with diffusion-based or flow-matching action policies for robots and action chunking.
  • Experience with reinforcement learning for robotics on real hardware, including sample-efficient methods, residual RL, or on-policy fine-tuning of foundation policies.
  • Strong programming skills in Python and production-level experience with PyTorch and ML training infrastructure.
  • Practical experience with NVIDIA Isaac Sim / Isaac Lab, MuJoCo, or equivalent robotics simulation tools.
  • Comfort working directly with physical robots for debugging, iteration, and deployment.
  • Strong communication skills and ability to explain complex technical concepts to diverse audiences.
  • Preferred: experience with edge inference on hardware such as TensorRT, ONNX, or FP16 / INT8 quantization for real-time on-robot deployment.
  • Preferred: experience with visual self-supervised representation learning on robot or 3D vision tasks.
  • Preferred: legged-robot or whole-body control experience, including locomotion, manipulation on a floating base, or quadruped/humanoid integration.
  • Preferred: experience with physics-informed ML or hybrid models constrained by known physics.
  • Preferred: experience building ML pipelines or infrastructure in a team setting.

Benefits

  • Daily free lunch.
  • Flexible PTO.
  • Comprehensive medical, dental, and vision coverage.
  • 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents.
  • 401(k) retirement plan through Empower.
  • Generous employee referral bonuses.

Interested in this position?

Apply directly on the company website

Apply Now

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