Lead the development of fleet deployment and testing infrastructure for robotics software at Mind Robotics.
Posted by employer 2 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 10 hours ago
Skills & Technologies
Role intensity
50% coding
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
In this role at Mind Robotics, the Tech Lead focuses on developing and maintaining the infrastructure necessary for deploying and managing robotic systems in industrial settings. Key skills include proficiency in Python or Rust/C++, experience with fleet management systems, and a strong background in integration testing and CI/CD pipelines. This position is ideal for a seasoned engineer who thrives on tackling complex challenges and has a proven track record in scaling deployment processes. Mind Robotics emphasizes hands-on problem-solving, making it a fitting environment for those passionate about robotics and physical AI.
Joblaze insights
Quick facts
From the original posting
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.
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
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
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
Standard company text repeated across Mind Robotics's postings is omitted here.