Senior Machine Learning Engineer Tech Lead Robot Learning Loco Manipulation

Skills

About the Role

You will set technical direction and architecture for a whole-body loco-manipulation stack. You will design hybrid physics-machine-learning systems, lead core learning and policy workstreams, partner across hardware and deployment functions, mentor engineers, establish engineering standards, and write production-quality code.

Requirements

• PhD or Master’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field, or equivalent experience.
• 5+ years of hands-on robot-learning experience.
• Experience shipping sim-to-real policies on real robots.
• Demonstrated technical leadership and mentorship.
• Deep sim-to-real expertise, including domain randomization, system identification, teacher-student distillation, and sim-to-online fine-tuning.
• Experience with simulation construction, policy training, data collection, real-world deployment, and failure diagnosis.
• Physics-informed machine learning or hybrid-control experience.
• Python and C++ programming skills.
• Experience setting technical direction in a tech-lead capacity.

Responsibilities

• Set technical direction for machine-learning architecture, training methodology, data strategy, and deployment.
• Own architectural workstreams across action-policy learning, world-model-based supervision, and policy-orchestration interfaces.
• Design hybrid physics-machine-learning architectures for the loco-manipulation stack.
• Own cross-functional partnerships and drive a phased deployment strategy.
• Mentor junior and intermediate engineers.
• Establish code-quality standards, review practices, and engineering norms.
• Write production-quality code.

Benefits

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