Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

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.

Responsibilities

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.

Requirements

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.

Skills

Portable demonstration interfaces
Instrumented task tools
VR
Motion capture
Haptics
Retargeting
Remote robot operation
Shared autonomy
Imitation learning
Reinforcement learning
Active learning
Failure-directed data collection
Networked real-time systems
Video transport
Time synchronization
Edge data capture

Location

San Francisco

Work Type

On-site

Experience Level

Senior

Education Level

Bachelor's degree

Salary/Compensations

$170,000–$220,000

About the Company

GRAM is a self-replication company creating machine labor for the physical economy.
Our first research frontier is self-preservation: the base case of physical self-replication.
We are building a new class of machines called insectoids that can survive, coordinate, and recover without humans.
We believe scalable machine labor requires more than single-agent task generality or machines shaped in our image.