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

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.
• 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.

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. You have shipped sim-to-real policies on real robots, across different tasks or platforms.
• Deep sim-to-real expertise - domain randomisation, system identification, teacher-student distillation, sim-to-online fine-tuning. You can design a transfer strategy for a novel problem.
• Full-stack robot learning - fluent across simulation construction, policy training, data collection, real-world deployment, and failure diagnosis.
• Physics-informed ML or hybrid control experience - PINNs, neural ODEs, MPC with learned dynamics, process-model-conditioned generation, or similar.
• A defensible view on visual-reasoning-centric substrates for grounded spatial / physical reasoning.
• Push-back willingness - you can defend a non-obvious architectural commitment under pressure, and change your mind on evidence.
• Strong programming skills in Python and C++; production-quality code with reproducibility, testing, and maintainability discipline.
• Strong communication skills, able to convey complex technical concepts to a diverse audience.
• Demonstrated independent technical authority - you have set technical direction in a tech-lead capacity, leading a research subgroup, owning an architecture across multiple ICs' work, or making the architectural call on a high-profile project.
• Strongly Preferred:
• Edge inference depth (TensorRT, ONNX, edge-class deployment).
• Loco-manipulation experience - locomotion, whole-body control, and manipulation on legged platforms (quadrupeds, humanoids). The coupling between the three is the hard problem; direct hands-on experience or a defensible architectural view both count.
• Precision manipulation or surgical robotics - sub-mm accuracy tasks.
• Flow-matching action-head design at depth - direct experience with the architectural pattern.
• Visual self-supervised representation learning experience on robot or 3D-vision tasks.
• Multi-skill workflow or hierarchical policy design - skill sequencing, failure detection, control mode transitions.
• Experience building ML capability from ea

Benefits

Additional Information

Build the Path Forward At Path Robotics, we're building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use. Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together. We are standing up a new Robot Learning team focused on whole-body loco-manipulation for precision tasks in heavy manufacturing. We are seeking a Senior Machine Learning Engineer (Tech Lead) for this new team. You write code, set the technical direction, make the architectural decisions the team builds on, mentor junior and intermediate engineers, and help shape how the team works.

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