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

Path Robotics· Engineering
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Columbus, OH; Remotefull-timePosted 2mo ago

About the role

Senior ML Engineer (Tech Lead) for a new Robot Learning team focused on whole-body loco-manipulation for precision tasks in heavy manufacturing. Leads technical direction, architectural decisions, mentorship, and collaboration with hardware and domain teams to deploy production-grade robot learning systems.

Responsibilities

  • Set the ML technical direction for the team, architectural choices on perception, reasoning, and action generation; training methodology; data strategy; the path from research bet to deployed capability.
  • Own the architectural workstreams that define the team's research and engineering bets — multiple core build streams across action-policy learning, world-model-based supervision, and policy-orchestration interfaces.
  • Design hybrid physics-ML architectures for the integrated loco-manipulation stack, ensuring whole-body coordination and real-time compensation for base motion.
  • Own cross-functional partnerships with hardware teams, domain experts, customer-facing assurance standards, and upstream/downstream teams; drive phased deployment strategy.
  • Mentor and shape the team, establish code-quality standards, review practices, and engineering norms; write code and actively contribute as a tech-lead.

Qualifications

  • Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related field or equivalent experience.
  • 5+ years of hands-on robot learning experience with sim-to-real policies on real robots across different tasks or platforms.
  • Demonstrated technical leadership and mentorship; experience making architectural decisions and shaping junior engineers as a tech lead.
  • Deep sim-to-real expertise — domain randomisation, system identification, teacher-student distillation, sim-to-online fine-tuning.
  • Full-stack robot learning experience — simulation construction, policy training, data collection, real-world deployment, failure diagnosis.
  • Physics-informed ML or hybrid control experience — PINNs, neural ODEs, MPC with learned dynamics, etc.
  • Defensible view on visual-reasoning-centric substrates for grounded spatial/physical reasoning.
  • Ability to defend architectural choices and adapt based on evidence.
  • Strong programming skills in Python and C++; production-quality, reproducible, well-tested code.
  • Strong communication skills and ability to convey complex concepts to diverse audiences.
  • Independent technical authority in a tech-lead capacity.

Skills

Required:ML technical directionArchitectural leadershipHybrid physics-ML architecturesCross-functional collaborationMentorship

Benefits

  • Daily free lunch
  • Flexible PTO
  • Comprehensive medical, dental, and vision coverage
  • 6 weeks fully paid parental leave, + 6–8 weeks for birthing parents (12–14 weeks total)
  • 401(k) retirement plan through Empower
  • Generous employee referral bonuses
Last updated Aug 7, 2026. Interested? Apply on the company site.

About Path Robotics

Path Robotics | Physical AI for Manufacturing

Path Robotics – Physical AI for manufacturing. Obsidian, our foundational AI, powers Path's Intelligent Welding Cells and Rove. 4x productivity, 30%+ lower cost, $0 capex.

Welding CellsRoveObsidianPhysical AIManufacturingAutomation
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