Robotics Lead — Policy-Driven Automation & Team Growth

Zero RFI; Mountain View (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Zeromatter seeks a Robotics Lead to define and drive the robotics and physical AI roadmap, partnering with the Dynamics team to ensure high-fidelity simulation and rapid policy development. You will actively train and evaluate policies on real hardware while guiding a growing team and collaborating with customers to solve real manipulation challenges.

You will lead research into imitation learning, reinforcement learning, and foundation/VLA models, bridging simulation and real-world deployment,

Qualifications

• Engineering or related technical degree or equivalent hands-on experience.
• Deep, hands-on experience developing and deploying robot learning systems on physical hardware.
• Experience taking policies from simulation to real-world deployment, addressing domain gaps.
• Demonstrated technical leadership including defining roadmaps and growing a team.

Responsibilities

• Define and own Zeromatter's robotics and physical AI roadmap in partnership with the Dynamics team.
• Grow the Robotics team by hiring and mentoring as the group scales.
• Engage directly with customers to scope use cases and drive end-to-end proof-of-concept work.
• Lead state-of-the-art robot learning research, including imitation and reinforcement learning.
• Hands-on training and evaluation of robot learning policies on Zeromatter's platform and hardware.
• Collaborate with the Dynamics team to identify simulation capabilities that close the sim-to-real gap.
• Define user-facing workflows and tooling for training, evaluating, and deploying robotics policies.

Tools

Python

Rust

C++

Job description

Zeromatter seeks a Robotics Lead to define and drive the robotics and physical AI roadmap, partnering with the Dynamics team to ensure high-fidelity simulation and rapid policy development. You will actively train and evaluate policies on real hardware while guiding a growing team and collaborating with customers to solve real manipulation challenges.

You will lead research into imitation learning, reinforcement learning, and foundation/VLA models, bridging simulation and real-world deployment,