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

Path Robotics is building AI-driven robotic systems for embodied intelligence that adapt, learn, and operate in real-world environments. The Senior Machine Learning Engineer (Tech Lead) will set the technical direction for a new robot learning team focused on whole-body loco-manipulation, while designing architectures, guiding deployment strategy, mentoring engineers, and contributing code.

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. As one of the first senior hires, you are designing the approach, not extending it
• 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. Manipulation, locomotion, and the whole-body control coupling between them are not separable on legged platforms; sub-millimetre continuous-trajectory precision at the tool requires the whole-body controller to compensate for base motion in real time. Today on fixed bases; tomorrow on mobile platforms. The integration is the hard problem; you own its design
• Own the cross-functional partnerships with hardware teams, domain experts, customer-facing assurance standards, and upstream / downstream teams. Drive a phased deployment strategy that builds production trust over time
• Mentor and shape the team, guide junior and intermediate ICs across software, ML, robotics, and perception backgrounds; establish code-quality standards, review practices, and engineering norms; help identify and attract next hires. You write code throughout — this is a tech-lead role, not a step away from the work