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Applied Intuition is building a robot learning platform (Dana) that provides the data infrastructure and training intelligence for robots to learn industrial tasks. The robotics team works hands-on with hardware to deliver robot autonomy on customer lines, training, evaluating, and deploying policies on real robots doing real industrial tasks.
As a Robot Infrastructure Engineer focused on collection tooling, you will make high-quality robot demonstrations and human corrections easy to capture and use. This is a tooling role, not a role running a large collection operation. You will work on the teleoperation workflows, quality checks, and ingestion tools that turn a session at the robot into training data the team can trust.
Key responsibilities include:
- Building teleoperation and operator tools for leader arms, VR, and other interfaces, including calibration, action mapping, latency, and reliable recording
- Implementing episode workflows for task instructions, start/stop, resets, annotations, success labels, and human takeover, maintaining clean boundaries between policy actions and human corrections
- Building collection quality checks for frame drops, timestamp alignment, missing signals, calibration validity, and incomplete episodes with immediate operator feedback
- Building collection specifications and adapters that validate data from external partners against task requirements, schemas, calibration, and provenance
- Keeping raw recordings as the source of truth and making normalization and export to training formats reproducible
- Showing collection progress and coverage against the task so the team collects missing variations and hard cases
- Testing everything on real robots and documenting setup and troubleshooting for engineers, operators, and partners
Applied Intuition is a $15 billion Series A company founded in 2017, headquartered in Sunnyvale with offices globally. It serves automotive, defense, trucking, construction, mining, and agriculture industries. Eighteen of the top 20 global automakers and the US military trust the company's solutions.
The company expects full-time employees to work in-office 5 days per week, with flexibility for occasional remote work and schedule adjustments for family commitments.
REQUIREMENTS:
- Built data collection, teleoperation, sensor recording, or human-in-the-loop tooling used on real robots or autonomous systems, and validated it on hardware
- Strong Python skills and software engineering fundamentals, including APIs, tests, versioned schemas, and debugging data pipelines
- Experience with synchronized video, robot state, actions, or other multimodal time-series data
- Working knowledge of coordinate frames, sensor calibration, data provenance, and how collection errors show up in trained models
- Experience building tools for other people, watching them fail in real use, and simplifying without hiding data-quality problems
- Ability to turn a task description into an executable collection workflow together with learning, hardware, and operations colleagues
NICE TO HAVE:
- Experience with ROS 2, MCAP, LeRobot, HDF5, or adapters between robotics datasets
- Experience with VR teleoperation, leader-follower systems, motion retargeting, haptics, or takeover-based learning
- Experience building video and trajectory inspection, annotation, dataset validation, or data grading tools
- Experience with sensor fusion, offline trajectory reconstruction, coverage analysis, or active data collection
