About Genesis

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 Do

• Turn customer workflows into clearly scoped deployments, using site visits and operator interviews to define requirements, success metrics, and acceptance criteria.

• Build deployment financial models and assess customer value, utilization, implementation costs, and support needs to inform scope and rollout decisions.

• Partner with Deployment Solution Engineers, research, engineering, and safety specialists to align technical capabilities with customer requirements and site readiness.

• Drive cross-functional execution from scoping through customer acceptance, keeping milestones, dependencies, scope changes, and decisions clear across distributed teams.

• Coordinate acceptance testing, training, and handover, and turn field feedback and competitive insights into reusable deployment practices.

What You'll Bring

• A track record of taking complex technical initiatives from ambiguous customer needs through launch and adoption.

• Strong analytical judgment, with experience building financial models and evaluating costs, resource constraints, and implementation tradeoffs.

• Enough technical fluency to work with robotics, software, and AI teams, question assumptions, and translate field issues into clear requirements.

• A strong bias toward the field, with the ability to learn directly from operators and communicate requirements, decisions, and tradeoffs clearly in writing.

• Comfort driving alignment and execution with incomplete information across customers, engineers, and external partners.

• Bonus: Experience in robotics, autonomy, industrial technology, or enterprise systems where success depends on reliable real-world performance.