Mind Robotics
Application Engineer
Palo Alto
Sponsorship not specifiedDetected 19 days ago
Machine LearningData EngineeringRoboticsSensorsResearchCommunicationCollaboration
About the role
- your job is to help harden and productionize them for scale - from 10 capture stations at one site to hundreds across multiple OEM plants, and from a handful of teleop stations to a multi-shift fleet.
- This is early, hands-on, 0-to-1 engineering: you'll ship code that runs on real hardware in real factories, and see its effect on robot behavior.
- Ship the teleop stack - collection, evaluation, and operator tooling for our teleoperation stations, including metrics, task management, and the workflows our robot operators use every day
Responsibilities
- Build the field capture stack - edge software for our data collection rigs: device management, sensor orchestration, and real-time data quality monitoring that holds up on a factory floor
- Support the field - debug issues on live systems, instrument for observability, and work directly with site operations staff and robot operators who depend on your software
Requirements
- Experience with at least one of: real-time data pipelines, edge computing, device or fleet management, robotics or sensor systems
Nice to have
- Hands-on experience with sensor data (video, depth, IMU, force/torque) and the infrastructure to process it at scale is a plus
- Background in robotics, autonomous vehicles, industrial IoT, or teleoperation systems is a plus
- Exposure to manufacturing or other industrial environments is a plus
- Familiarity with ML data workflows (datasets, labelling, evaluation) is a plus
Company info
- Mind Robotics is building robots that learn from real-world experience - and the quality of that experience starts with how we collect and process data.
- Our field data collection system puts capture rigs on the factory floor at manufacturing sites, generating the raw sensor data that trains everything downstream.
- Our teleoperations program turns human demonstrations into the high-quality data that grounds our AI models in physical reality.
- Both flow through annotation and quality control into our training platform.
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