Ai Data Operations Lead
Roboforce
Milpitas
- Own the operational execution of RoboForce's AI learning programs, translating research priorities into scalable execution plans.
- Partner closely with AI researchers and engineers to coordinate cross-functional execution across AI, Hardware, Robotics Software, and Operations.
- Recruit, develop, and retain a 20–50 person team across data collection, annotation, and teleoperation — setting clear performance expectations, building career development pathways, and fostering a culture of ownership, safety, and continuous improvement.
- Define, track, and report operational KPIs — including data collection throughput, robot uptime, and evaluation turnaround — to drive decisions and communicate operational health to leadership.
- Own robot fleet health and readiness — driving preventive and corrective maintenance, and tracking uptime to ensure robots are mission-ready for data collection and evaluation.
- Drive program execution, resolve blockers, manage priorities, and continuously improve operational efficiency.
- Own end-to-end execution of robot data collection and annotation programs, including operational workflows, SOPs, operator training, scheduling, quality assurance, and vendor management.
- Build scalable operational processes that consistently deliver high-quality datasets supporting AI development.
- Partner with AI researchers to organize evaluation resources, execute testing plans, and deliver timely, reliable evaluation results.
- Ensure experiment outcomes, operational learnings, and program progress are accurately captured and communicated across cross-functional teams.
- Foster a culture of operational excellence, ownership, and continuous improvement while establishing scalable operational processes that enable the AI organization to grow.
- Bachelor's degree or above; technical degrees preferred.
- 5+ years of experience in technical operations, program management, or cross-functional operations leadership, ideally in a hardware, robotics, or R&D environment.
- Demonstrated experience managing people, operators, or vendor teams — including hiring, training, scheduling, and performance management.
- Strong ability to translate technical priorities from research and engineering teams into scalable operational workflows, SOPs, and execution plans, without needing to write code or design systems yourself.
- Comfortable partnering closely with AI researchers and engineers, and fluent enough in technical concepts (data pipelines, model training, robot operations) to coordinate effectively — but this is a people and process leadership role, not a hands-on engineering role.
- Excellent communication, organizational, and cross-functional leadership skills.
- Comfortable operating in a fast-paced, ambiguous R&D environment where priorities shift quickly.
- Requires 5 days/week in-office collaboration with the teams.
- Experience supporting Physical AI, robot learning, imitation learning, or VLA development.
- Experience with teleoperation systems, human demonstration pipelines, or robotics data collection.
- Experience managing large-scale annotation operations and external vendors.
- Familiarity with robot benchmarking and evaluation workflows.
- Experience designing internal operational tools, dashboards, or workflow automation systems.
- Competitive stock options/equity programs.
- Health, dental, and vision insurance, 401(k) plan.
- Visa sponsorship and green card support for qualified candidates.
- Lunches and dinners, a fully stocked kitchen, and regular team-building events.
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