Senior Machine Learning Engineer, Robot Learning

Salary: $94,000 - 134,000 per year Requirements:

• We expect a Ph.D. or masters degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a closely related discipline, or equivalent practical experience.
• We require 5+ years of hands-on robot learning experience, including shipping sim-to-real policies on physical robots across multiple tasks or platforms.
• We need proven technical leadership and mentorship experience, with a track record of making architectural decisions that others have built upon and guiding more junior engineers.
• We value deep sim-to-real expertise, including domain randomization, system identification, teacher-student distillation, and sim-to-online fine-tuning.
• We look for full-stack robot learning capability across simulation building, policy training, data collection, real-world deployment, and failure analysis.
• We expect experience with physics-informed ML or hybrid control approaches such as PINNs, neural ODEs, MPC with learned dynamics, or related methods.
• We want a defensible perspective on visual-reasoning-centric foundations for grounded spatial and physical reasoning.
• We need someone who can challenge assumptions when needed, defend non-obvious architectural choices, and update their view based on evidence.
• We require strong Python and C++ programming skills, with production-quality habits around reproducibility, testing, and maintainability.
• We expect clear communication skills and the ability to explain complex technical concepts to a broad audience.
• We value independent technical authority demonstrated through setting direction in a tech-lead role, leading research subgroups, or owning architecture across multiple contributors.
• Strongly preferred: edge inference experience with TensorRT, ONNX, or similar deployment stacks.
• Strongly preferred: experience with loco-manipulation on legged platforms, including locomotion, whole-body control, and manipulation.
• Strongly preferred: precision manipulation or surgical robotics experience involving sub-millimeter accuracy.
• Strongly preferred: hands-on flow-matching action-head architecture experience.
• Strongly preferred: visual self-supervised representation learning on robot or 3D vision tasks.
• Strongly preferred: multi-skill workflow or hierarchical policy design, including skill sequencing, failure detection, and control-mode transitions.
• Strongly preferred: experience building ML capability in an early-stage environment or creating research infrastructure from scratch.

• We will have you define the ML technical direction for the team, including perception, reasoning, action generation, training methods, data strategy, and the path from research ideas to deployed capability.
• You will own key architectural workstreams shaping our research and engineering bets, including action-policy learning, world-model-based supervision, and policy-orchestration interfaces.
• You will design hybrid physics-and-ML architectures for an integrated loco-manipulation stack, solving the coupling between manipulation, locomotion, and whole-body control.
• You will lead cross-functional collaboration with hardware teams, domain experts, customer assurance stakeholders, and upstream and downstream partners.
• You will drive a phased deployment approach that steadily builds trust in production systems over time.
• You will mentor junior and intermediate engineers across software, ML, robotics, and perception backgrounds.
• You will establish code quality standards, review practices, and engineering norms.
• You will help identify and recruit future team members.
• You will continue writing code as part of the role; this is a hands-on tech-lead position.

• 3D
• AI
• Fine-tuning
• Flow
• Hardware
• Python
• Robotics
• Machine Learning
• Mobile

More:

We are Path Robotics, building the future of embodied intelligence with AI-driven systems that help robots adapt, learn, and operate in the real world while closing the skilled labor gap and transforming industries. We are forming a new Robot Learning team focused on whole-body loco-manipulation for precision tasks in heavy manufacturing. Our team is made up of intelligent, humble, driven people who enjoy tackling big, difficult problems together. We offer daily free lunch, flexible PTO, comprehensive medical, dental, and vision coverage, 6 weeks of fully paid parental leave plus an additional 6 to 8 weeks for birthing parents, a 401(k) retirement plan through Empower, and generous employee referral bonuses. We value ideas, welcome unique thinking, and are committed to building a diverse, inclusive, and equal-opportunity workplace.

last updated 33 week of 2026