Tech Lead, Software Infrastructure and Fleet Management

About Mind:

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.

 

The Role:

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 software systems for fleet deployment, CI/CD infrastructure, and observability for our field-deployed robots. This is an IC-heavy role: you're building these systems yourself.
A DevOps engineer will support you in this work.
This is a role for someone who wants to make our deployed robots more capable and our engineers more effective, by owning the hardest problems in getting robotics software safely and reliably into production at scale.

Responsibilities:

• Architect fleet-wide deployment: OTA package delivery, versioned rollouts, staged/canary release, rollback strategies, and configuration management across heterogeneous robot hardware in the field, working with the firmware team, who own the on-robot update process

• Build observability for the fleet: diagnostics, monitoring, and alerting that surface robot and deployment issues early, with the logging infrastructure and visualization tooling behind them

• Own the build system (Bazel, SCons, Buck2, or similar) that produces reproducible, versioned software packages for engineering use and production robot deployment, including dependency management and build performance

• Contribute to and interface with hardware-in-the-loop (HIL) and software-in-the-loop (SIL) test infrastructure, and build the pre-deployment validation gates that use its results to catch failures before they reach a live site

• Build and evolve the fleet management platform 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, from build system through OTA package creation, deployment, and status monitoring

• Set technical standards and do deep design/code review across deployment, testing, and dev ops

Requirements:

• Strong software engineering in Python and/or Rust/C++, with experience building tooling and services that improve developer productivity

• Experience building backend services and APIs for device fleets: artifact storage, OTA package creation, versioning schemes, staged rollout and rollback orchestration, device state tracking, and remote configuration management across many physical devices

• Experience with system test infrastructure 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

• Build and packaging systems (Bazel, SCons, Buck2, or similar), containerization, and edge orchestration (Docker, and edge-appropriate orchestration/agent frameworks) for building 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

Nice to Have:

• 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