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Salary: USD 168,000 - 219,000 / annual
Agility Robotics is seeking a Manager of Data Collection to lead and scale the team responsible for teleoperation data collection that supports robot learning. This role owns the daily operating rhythm of data collection operations, treating it as a production function with measurable output that directly gates AI model progress.
TEAM LEADERSHIP & TALENT
You will build, train, and lead the data collection team including robot operators and data collection specialists in Fremont. You own hiring for the function—defining operator profiles, building interview processes, and scaling the team against collection demand. You develop onboarding and ongoing training programs including certification on teleoperation rigs, capture hardware, and task protocols to ensure consistent operator output across people and shifts. You manage shift scheduling and coverage to match campaign demand, including extended hours or weekend coverage when program milestones require it. You build career paths from data collection into system test, robot operations, and other technical roles. You promote a culture of safety including proper use of teleoperation and capture equipment, ergonomics, and adherence to safety procedures.
DATA COLLECTION OPERATIONS & THROUGHPUT
You own day-to-day readiness of teleoperation stations, capture rigs, robots, and workcells used for data collection, coordinating with engineering and technical support on calibration, configuration, and return to service. You plan and execute collection campaigns against task taxonomy and volume targets set with AI Engineering, including scoping, scheduling, and progress reporting. You identify bottlenecks through workflow analysis, time studies, and capacity modeling, then drive practical fixes. You lead root cause analysis on recurring operational issues including rig downtime, capture failures, and protocol drift, and follow through on corrective actions. You create and maintain SOPs, work instructions, task protocols, and process controls, managing change control when protocols or hardware are updated. You support rollout of new capture hardware, sensors, and tooling in partnership with Engineering, Facilities, and Safety.
DATA QUALITY & KPI OWNERSHIP
You own and report core operating metrics for data collection: episode throughput per operator hour and per shift, usable episode yield and rejection rate, station utilization, rig uptime and downtime, cycle time, operator productivity, and cost per usable episode. You define and enforce the quality bar in partnership with AI Engineering, including what makes an episode usable, and drive first-pass yield up over time. You track coverage against the target task and scenario taxonomy so gaps are visible before they block model work. You build dashboards and reporting that give AI Engineering and leadership live visibility into collection volume, quality, and capacity without having to ask. You use operational data to drive continuous improvement in throughput, quality, and unit cost.
VENDOR & CONTRACT LABOR MANAGEMENT
You own vendor and contract labor relationships supporting data collection, including sourcing, scoping statements of work, rate negotiation, onboarding, and offboarding. You define and manage vendor performance against quality, throughput, and SLA commitments, holding vendors accountable to the same metrics as internal staff. You manage the mix of internal and contract capacity to flex with campaign demand while protecting data quality and continuity. You evaluate external data collection service providers where in-house capacity is not the right answer, and make build versus buy recommendations with supporting cost and quality data.
PARTNERSHIP WITH AI ENGINEERING
You partner with AI, Perception, and Skills engineering teams to translate the model roadmap into concrete collection plans: which tasks, which scenarios, how many episodes, at what quality bar, by when. You serve as the operational point of contact for new data collection projects, from scoping through delivery. You close the loop with AI Engineering on which collected data actually improved policy performance, and use that to reprioritize collection rather than optimizing volume alone. You translate engineering data requirements into operator-executable protocols, and translate operator-observed issues back into engineering terms.
WORKING CONDITIONS
This is an onsite position in Fremont, CA, five days per week. The role involves time on the floor, standing for extended periods, supervising shifts, and responding to urgent operational issues. Occasional travel to offsite collection locations or other Agility sites is expected.
REQUIREMENTS
- 6+ years of experience in technical operations, data operations, manufacturing, industrial or process engineering, lab operations, or production environments
- 3+ years of experience leading frontline or technical teams, including hiring, performance management, and mentoring
- Familiarity with teleoperation rigs, VR and XR capture setups, motion capture, or wearable sensor capture
- Experience running a metrics-driven operation, with accountability for throughput, quality, and utilization targets
- Experience managing vendors or contract labor, including performance and SLA management
- Experience operating and troubleshooting early-stage technology in a fast-moving environment with frequently changing priorities
- Strong command of operating KPIs such as throughput, cycle time, takt time, utilization, yield, OEE, and uptime
- Ability to build operational dashboards and reporting, and to communicate using data rather than anecdote
- Comfort with data pipeline and data quality concepts, including how collected data is validated, labeled, and delivered to downstream consumers
- Experience with tools such as JIRA, Confluence, Grafana, Tableau, Power BI, Google Workspace, or equivalent platforms
- Bachelor's degree in Engineering, Operations, Industrial Engineering, or a related technical field, or equivalent practical experience
PREFERRED QUALIFICATIONS
- Experience establishing and growing a teleoperation or robot data collection function at another robotics, humanoid, autonomous vehicle, or embodied AI company
- Working understanding of imitation learning and robot learning data requirements, sufficient to hold a substantive conversation with AI engineers about what data is worth collecting
- Experience with Lean, Six Sigma, time studies, or similar process improvement methods
