- Robot type
- Industrial Automation
- Location
- Palo AltoCaliforniaUSA
- Job type
- Software
- Posted
- Aug 24, 2026
Full-time
Tech Lead, Software Infrastructure and Fleet Management
Job description
Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.
Job responsibilities
- Architect fleet-wide deployment: OTA updates, versioned rollouts, staged/canary release, rollback strategies, and configuration management across heterogeneous robot hardware in the field
- Design and build testing infrastructure — hardware-in-the-loop (HIL) test reporting, simulation-based regression testing, and pre-deployment validation gates that catch failures before they reach a live site
- Build and evolve the fleet management platform — the tooling, dashboards, and APIs used to track robot inventory, software/config versions, health state, and deployment status across every unit and site
- Own CI/CD pipelines that gate deployment on more than unit tests, and the full path from build artifact to a running process on a physical robot at a remote site
- Set technical standards and do deep design/code review across deployment, testing, and dev ops
- Work directly with engineering and research teams to build tools and systems that increase team velocity
- Design logging infrastructure & visualization tooling
Job requirements
- Strong software engineering in Python and/or Rust/C++, with experience building tooling and services
- Experience with fleet/device management systems: OTA update mechanisms, versioning schemes, staged rollout and rollback design, and remote configuration management across many physical devices
- Hands-on experience with integration and systems testing for hardware-attached software — hardware-in-the-loop testing, simulation-based regression suites (Isaac Sim, Gazebo, MuJoCo, or similar), and CI/CD pipelines…
- Observability engineering for edge/field deployments: telemetry pipelines, structured logging, and alerting
- Containerization and edge orchestration (Docker, and edge-appropriate orchestration/agent frameworks) for packaging and deploying software onto heterogeneous robot compute
- Track record of taking deployment/testing systems from ad hoc to reliable, repeatable process as the number of deployed units and sites grows