Senior Data Operations Manager

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.

The hardest part of building general-purpose robots is not the model. It is the data: real, dexterous, physical-world manipulation that does not live on the internet. Our unlock is a data-collection glove built to the exact geometry of our robot hand, unobtrusive enough that a person can wear it through a normal workday, so ordinary work becomes training data that transfers to the robot without loss.

Paired with our own hardware, simulation, and models in one tight loop, that is the most scalable manipulation data engine in the world.

This is the role that runs that engine on the ground. You will own the system that turns stations, workforce, and facilities into one reliable operation, end to end, from the operator at the station to the accepted hour that lands in training. You will grow it from a single floor into a global, multi-shift operation that holds a world-class quality bar as it scales.

We are looking for someone who has run data collection at scale and is hungry to do it again at the frontier of physical AI.

• Run the floor end to end. Own scheduling, operator utilization, station uptime, and the throughput that delivers accepted hours at the quality bar, every week.

• Build the operator bench. Recruit, level, and develop operators and the senior operators who run shifts, until the team is deep enough for multiple shifts and multiple sites.

• Hold one standard everywhere. Make every floor we run and every partner site collect to the same playbook, the same metrics, and the same bar.

• Turn problems into process. Root-cause what slows the floor and ship the SOPs, layouts, and tooling that make the next site ramp faster than the last.

• Partner on quality and annotation. Work hand in hand with the Quality and Process and Annotation functions so collected hours convert cleanly into training-ready data.

• Stand up partner-site collection. Rehearse and run the mock-runs and first deployments that bring partner operators onto our gear.

• Report the truth. Build the reporting that tells the company, honestly, what we collected, at what quality, and at what cost.

• You have built data collection at scale, and it shows. You have run a teleoperation, glove, or human-data operation at a frontier robotics lab, an embodied-AI company, or a top data operation, and you know the difference between hours collected and hours that actually train a model. There is a short list of places this work happens. If you have done it, we want to talk.

• Throughput is in your blood. Scheduling, utilization, yield, and the hundred details of a working floor are second nature.

• Quality is never optional. You have run an operation where the bar was real and measured, and you held it without slowing the line.

• You run through walls. Bias for action, deep ownership, and a refusal to wait for permission. You see what needs doing and make it happen.

• You build teams that win. You hire…