Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for AI Data Operations Lead to lead and own the engineering of systems that turn embodied AI into real-world robot behavior.

You will be the technical owner and lead for the full embodied systems stack — the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning system — driving the direction hands-on and closing the loop between data, models, and action in the physical world.

Responsibilities

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.

Requirements

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.

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.