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Senior Machine Learning Engineer (Tech Lead), Robot Learning, Loco- Manipulation

2 weeks, 1 day ago
United States
Full-time
Lead
Machine Learning Engineer
Artificial Intelligence and Machine Learning
C++ Machine Learning Python 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 36

Description

  • Set the team’s ML technical direction across perception, reasoning, action generation, training methodology, data strategy, and deployment approach.
  • Own architectural workstreams spanning action-policy learning, world-model-based supervision, and policy-orchestration interfaces.
  • Design hybrid physics-ML architectures for an integrated loco-manipulation stack that combines manipulation, locomotion, and whole-body control.
  • Lead cross-functional collaboration with hardware teams, domain experts, customer assurance stakeholders, and upstream/downstream teams.
  • Drive a phased deployment strategy that builds production trust over time.
  • Mentor junior and intermediate engineers across software, ML, robotics, and perception backgrounds.
  • Establish code quality standards, review practices, and broader engineering norms for the team.
  • Help identify, attract, and hire future team members.
  • Write production code as a hands-on technical leader.
  • Shape how the new team works operationally and technically.

Requirements

  • Ph.D. 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 across different tasks or platforms.
  • Demonstrated technical leadership and mentorship in academia or industry.
  • Deep sim-to-real expertise, including domain randomization, system identification, teacher-student distillation, and sim-to-online fine-tuning.
  • Full-stack robot learning experience across simulation construction, policy training, data collection, real-world deployment, and failure diagnosis.
  • Physics-informed ML or hybrid control experience, such as PINNs, neural ODEs, MPC with learned dynamics, or process-model-conditioned generation.
  • A defensible view on visual-reasoning-centric substrates for grounded spatial or physical reasoning.
  • Strong programming skills in Python and C++, with production-quality coding practices for reproducibility, testing, and maintainability.
  • Strong communication skills for explaining complex technical concepts to diverse audiences.
  • Ability to defend non-obvious architectural decisions under pressure and revise them based on evidence.
  • Independent technical authority demonstrated through leadership of a subgroup, ownership of an architecture, or similar tech-lead responsibility.
  • Edge inference experience with TensorRT, ONNX, or edge-class deployment, preferred.
  • Loco-manipulation experience on legged platforms such as quadrupeds or humanoids, preferred.
  • Precision manipulation or surgical robotics experience involving sub-millimeter accuracy tasks, preferred.
  • Flow-matching action-head design experience, preferred.
  • Visual self-supervised representation learning experience on robot or 3D vision tasks, preferred.
  • Multi-skill workflow or hierarchical policy design experience, preferred.
  • Experience building ML capability at an early-stage team or from scratch, preferred.

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 (12–14 weeks total).
  • 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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