About Generalist
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
About the role
Generalist is hiring a Robotics Operations Manager to lead and scale the on-site operations that produce high-quality data for our robotic foundation models. You’ll lead robot operators and shift leads, owning daily execution across staffing, robot readiness, and data collection. Working closely with research and engineering, you’ll turn evolving technical priorities into reliable workflows and build the processes and team capabilities needed to scale.
What you’ll do
Own daily robotics operations. Coordinate staffing, task scheduling, robot availability, and equipment readiness to deliver consistent data collection throughput and quality.
Lead and develop the team. Coach operators and shift leads, set clear expectations, and support hiring, onboarding, training, scheduling, and performance management.
Keep the lab ready and safe. Oversee robot setup, readiness checks, equipment tracking, and safe operating procedures. Stay close to the work on the lab floor, support basic troubleshooting, and coordinate repairs and technical escalations.
Translate research priorities into execution. Partner with research and engineering to launch, refine, and retire data collection tasks, with clear instructions, quality checks, and issue tracking.
Use operational data to improve performance. Establish metrics and reporting across robot utilization, throughput, data quality, operator productivity, and equipment reliability. Identify bottlenecks and recurring failures, then drive improvements with the relevant teams.
Build processes that scale. Develop practical operating procedures, training materials, and handoff routines that help the team execute consistently as the fleet and operation grow.
You might thrive here if you…
Have owned day-to-day execution in robotics, manufacturing, logistics, technical operations, or another hands-on environment where people and equipment must work together reliably.
Have led and developed frontline teams, including coaching people, setting performance expectations, and maintaining standards for quality and safety.
Are comfortable working around complex hardware and can assess an operational problem, guide initial troubleshooting, and recognize when engineering support is needed.
Have used metrics to identify a bottleneck or recurring issue and made changes that improved throughput, quality, or reliability.
Can turn changing technical requirements into clear instructions and daily priorities, making sound decisions and communicating tradeoffs when the process is still taking shape.
Helpful additional experience
Robotics, industrial automation, or managing and maintaining fleets of complex hardware.
AI/ML data collection, human-in-the-loop workflows, or quality assurance in a technical environment.
Building operational dashboards or using automation, scripting, or AI tools to improve workflows.