Senior Quality and Process Manager

Genesis AI; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Genesis AI is seeking a data-quality and process-lead role to own the metrics, acceptance standards, and QA systems that ensure high-quality data for model training. You will collaborate with collection, QA, and model teams to define and enforce criteria, driving continuous improvement across global sites.

The ideal candidate has 5–10 years leading data or quality teams, a track record building quality functions, and comfort with robotics or sensor-derived data.

Qualifications

• Five to ten years leading data, quality, or operational teams.
• Metric-driven with root-cause analysis and continuous improvement.
• Built a quality function and acceptance standard from scratch.
• Quality-first mindset that keeps throughput steady.
• Robotics or sensor-data fluency is a strong plus.

Responsibilities

• Own data-quality metrics. Own accuracy, consistency, rework rate, first-pass yield, and accept-rate every lane is measured against, and report them to leadership.
• Make the acceptance bar a written contract. Publish a versioned acceptance standard and a defect taxonomy every site grades against, so good is defined, not argued.
• Build the QA and audit system. Stand up the review pipeline, audit process, and escalation workflow that catch problems on the floor and at annotation, every day.
• Close the loop with operators fast. Run a feedback turnaround quick enough to change operator behavior the same week, and turn edge cases into guideline updates.
• Engineer and standardize the process. Turn how we collect into documented, repeatable work, so each site and station ramps faster than the last.
• Translate model needs into the bar. Be the point of contact between collection, QA, and the model team, turning what the model needs into clear acceptance criteria.

Skills

Data quality

Process ownership

SQL

Python

Six Sigma

Robotics data fluency

Job description

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 role

We have shipped a frontier model, a glove-and-hand stack built to one shared geometry, and Eno, and put it in front of the world, fast. That pace only holds if the data behind it is good enough to train on, every hour of it. This role owns the bar that makes it good.

You will define what a passing hour is, build the QA that enforces it, and engineer the standardized workflow that lets quality hold as we scale from one floor to a global operation. You will own the numbers, accept-rate, first-pass yield, rework, and cost per accepted hour, and tie them to model outcomes rather than paperwork. You will make our floor the kind of operation a world-class process engineer would recognize on sight.

What you'll do

• Own the data-quality metrics. Own accuracy, consistency, rework rate, first-pass yield, and the accept-rate every lane is measured against, and report them to leadership.

• Make the acceptance bar a written contract. Publish a versioned acceptance standard and a defect taxonomy every site grades against, so good is defined, not argued.

• Build the QA and audit system. Stand up the review pipeline, audit process, and escalation workflow that catch problems on the floor and at annotation, every day.

• Close the loop with operators fast. Run a feedback turnaround quick enough to change operator behavior the same week, and turn edge cases into guideline updates.

• Engineer and standardize the process. Turn how we collect into documented, repeatable work, so each site and station ramps faster than the last.

• Translate model needs into the bar. Be the point of contact between collection, QA, and the model team, turning what the model needs into clear acceptance criteria.

What we're looking for

• You have owned data quality and process at a serious operation. Five to ten years leading data, quality, or operational teams. At a frontier robotics lab, an embodied‑AI company, or a top data or labeling operation, you set the bar where it was real and raised it. There is a short list of places this discipline is done well. If you have built it, we want to talk.

• Metric-driven and analytical. You diagnose quality issues from data and ship corrective actions. Standard work, root-cause, and continuous improvement are how you think. Six Sigma or equivalent is a plus, and SQL or Python is a plus.

• You have built, not inherited. You have stood up a quality function and an acceptance standard where none existed.

• A quality-first mind, without becoming the bottleneck. You hold a hard bar and still keep the line moving.

• Robotics or sensor-data fluency. Experience with robotics, autonomy, or sensor-derived data is a strong plus.

How we work

We are always looking for people who are driven to work on hard problems and want to shape what the world will look like in ten years. A few of the values that guide us:

• Limitless ambition. We hold ourselves to the highest bar in everything we build.

• Relentless urgency. Iterate faster, learn faster. Time is the denominator.

• Type-2 Fun. Take the work seriously, not yourself. Embrace the grind and find joy in the struggle.

• Radical transparency. Candid communication builds trust, and direct feedback drives growth.

• Multiculturalism. We come from across the world. Be curious. Meet people on their terms.

• Team over ego. Help others, share context, and win as a team.

• A joyful journey. We take pride in the craft, enjoy the ride, and make space to laugh. Happiness is part of how we get there.