Senior Machine Learning Engineer (Tech Lead), Robot Learning, Loco- Manipulation
Path Robotics5 months ago
Responsibilities
- Set the team’s ML technical direction across perception, reasoning, action generation, training methodology, data strategy, and deployment.
- Own architectural workstreams for action-policy learning, world-model-based supervision, and policy-orchestration interfaces.
- Design hybrid physics-ML architectures integrating locomotion, manipulation, and whole-body control for fixed-base and mobile platforms.
- Own partnerships with hardware teams, domain experts, customer-facing assurance teams, and upstream and downstream teams.
- Drive a phased deployment strategy that builds production trust.
- Mentor junior and intermediate engineers, establish code-quality and review standards, shape engineering norms, and help attract future hires.
- Remain hands-on by writing production code throughout the role.
Requirements
- Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field, or equivalent experience.
- At least five years of hands-on robot-learning experience, including shipping sim-to-real policies on real robots across different tasks or platforms.
- Demonstrated technical leadership, architectural ownership, and mentorship of junior or intermediate engineers or researchers.
- Deep expertise in sim-to-real methods, including domain randomization, system identification, teacher-student distillation, and sim-to-online fine-tuning.
- Full-stack robot-learning experience spanning simulation construction, policy training, data collection, real-world deployment, and failure diagnosis.
- Experience with physics-informed ML or hybrid control, such as PINNs, neural ODEs, MPC with learned dynamics, or process-model-conditioned generation.
- Strong programming skills in Python and C++ and the ability to produce reproducible, tested, maintainable code.
- Strong communication skills and independent technical authority.
- Preferred experience with edge inference, TensorRT, ONNX, loco-manipulation on legged platforms, precision or surgical robotics, flow-matching action heads, visual self-supervised representation learning, hierarchical policies, and building early-stage ML infrastructure.
Benefits
- Daily free lunch.
- Flexible paid time off.
- Comprehensive medical, dental, and vision coverage.
- Six weeks of fully paid parental leave, plus an additional 6–8 weeks for birthing parents.
- 401(k) retirement plan through Empower.
- Employee referral bonuses.
Categories
ML EngineeringRobotics
About Path Robotics
Path Robotics builds AI-driven robotic welding systems that autonomously plan and execute welds for metal fabrication and industrial manufacturers. The privately held company, founded in 2014 and headquartered in Columbus, Ohio, sells turnkey welding cells and software with support services, and is expanding into naval and defense fabrication compliant with NAVSEA codes.