AI Data Operations Lead
On-siteMilpitas, California, United States
Job Summary
Lead operational execution of RoboForce's AI learning programs by translating research priorities into scalable execution plans and managing a 20–50 person team across data collection, annotation, and teleoperation. Define and track operational KPIs including data throughput and robot uptime, while owning end-to-end workflows for data collection, SOPs, and vendor management. Partner closely with AI researchers and engineers to coordinate cross-functional execution, organize evaluation resources, and ensure experiment outcomes are accurately captured. Drive program execution, resolve blockers, and continuously improve operational efficiency to maintain robot fleet health and readiness. Requires 5 days/week in-office collaboration within a fast-paced R&D environment.
Required Qualifications
- Bachelor's degree or above
- technical degrees
- 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
- fluent enough in technical concepts (data pipelines, model training, robot operations) to coordinate effectively
- 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
Desired Qualifications
- 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
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