Mind Robotics · San Francisco
Software EngineeringSoftware EngineeringFullTimeposted 2w ago
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.
At Mind Robotics, we're building generalized physical AI — robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. Deploying robots in real factories, reliably and safely, depends on the infrastructure that ships software to them, validates it before it goes live, and tells us when something's wrong once it's out there.
We're looking for a Tech Lead to own fleet deployment, testing infrastructure, and observability for our field-deployed robots. This is an IC-heavy role: you're building and hardening these systems yourself, not just defining processes for others.
This is a role for someone who wants to own the hardest problems in getting robotics software safely and reliably into production at scale, and ship them personally.
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
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 that gate on more than unit tests
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
Exposure to functional safety concepts relevant to physical systems
Background in electric vehicle OTA, industrial IoT, or other domains with similar field-reliability and fleet-management constraints
Experience scaling deployment/testing infrastructure