Senior Robotics Engineer, Data Collection

About the role

You will own the systems and methods that generate high-quality robot data from physical work, spanning demonstration, teleoperation, intervention, autonomous operation, instrumentation, operator tooling, scenario execution, and source-quality control. You will translate capability gaps into collection campaigns and use measured downstream results to decide what the machines should experience next.

This is a senior engineering role responsible for how experience is produced and validated at capture, including meaningful variation, failures, recoveries, and episode-level evidence. You also define the capture contracts that keep recorded experience usable for reproducible datasets and replay. Success means each campaign yields data that can change a training or evaluation decision—not operating hours without learning value.

What you will do

• Build field-capable demonstration interfaces and robust systems for teleoperation, intervention, autonomous rollout, and recovery-data collection in realistic physical work.
• Translate model failures and evaluation gaps into controlled scenarios, collection protocols, sampling priorities, and measurable acceptance criteria.
• Design operator interfaces with explicit command authority, latency budgets, feedback, safe handoff, and emergency behavior.
• Instrument demonstration tools, robots, operators, and environments so perception, action, timing, contact, intervention, and task outcome remain aligned and valid at capture.
• Commission collection stations and diagnose failures spanning sensors, controls, networking, operator input, robot execution, and recorded data.
• Define operator procedures, calibration checks, training, and escalation paths that produce consistent evidence across people and sessions.
• Measure whether collected experience changes model or system performance, then use the result to refine the next campaign.

Minimum qualifications

• Bachelor's degree in computer science, electrical engineering, mechanical engineering, robotics, or a related field, or equivalent practical experience.
• Strong C++ or Python programming ability in Linux, including experience with robot middleware, sensor streams, command interfaces, and hardware debugging.
• Direct experience building and repeatedly operating a teleoperation, shared-control, portable demonstration, instrumented task-tool, or robot-data collection system for physical work.
• Demonstrated ability to characterize end-to-end latency, timing, calibration, command safety, and data quality using instrumented tests.
• Experience converting a learning, test, or capability objective into a physical collection protocol whose data produced a measured change in model or system performance.

Preferred experience

• Portable demonstration interfaces, instrumented task tools, VR, motion capture, haptics, retargeting, remote robot operation, or shared autonomy.
• Imitation learning, reinforcement learning, active learning, or failure-directed data collection.
• Networked real-time systems, video transport, time synchronization, or edge data capture.

Compensation

The annual base salary range for this San Francisco position is $170,000–$220,000. An offer within this range will reflect the position's approved scope and the candidate's demonstrated role-relevant skills and experience.

Working at GRAM

This role is based on-site in San Francisco with continuous access to physical robots and collection systems.