We are a full-stack general-purpose robot company, born across San Francisco and Paris and bound by a single mission: to make general-purpose robots a reality, unlocking infinite physical labor for the world and freeing people for creativity, exploration, and the pursuits they love for their own sake.
We are French and American by birth and global by nature. We are backed by partners who share our vision, including Eclipse, Khosla Ventures, Bpifrance, and HSG, alongside Eric Schmidt, Xavier Niel, Daniela Rus, and Vladlen Koltun. Our people work across the Bay Area and Europe, building the engine that will teach robots to do real work in the real world. We recently unveiled Eno, our wheeled, dexterous robot powered by our GENE foundation model, and we are starting to put it to work with real customers.
What You'll DoOwn the product roadmap for our core Physical AI capabilities, translating research breakthroughs into deployable, customer-facing products.
Sit at the intersection of research, robotics engineering, and field deployment to turn ambiguous technical tradeoffs into clear product decisions.
Define what "ready for a customer site" actually means by setting success metrics, reliability thresholds, and scope boundaries for each release.
Drive cross-functional alignment across distributed teams in research, engineering, and field operations.
Track record of shipping technical products where the primary challenge was managing complex tradeoffs, not filling out roadmap slides.
Deep enough technical understanding to read a policy evaluation, understand a sim-to-real gap, or participate in complex debug sessions and ask the right questions without needing to write the code yourself.
Strong bias toward the field over the whiteboard, preferring to evaluate a failed pick on a live customer floor over reading ten synthetic benchmark reports.
Exceptional written communication skills to write specs and decision logs that hold up when you're not in the room.
Comfort operating with incomplete information in a fast-moving, pre-paradigm field where answers aren't obvious.
Bonus: Prior experience in robotics, autonomy, or another domain where "works in the lab" and "works in the world" carry vastly different bars for success.
