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.
A a Software Engineer on Edge & Field Systems, you'll be one of the founding engineers on the team that owns our application layer, reporting to our Head of Application Engineering. The systems work today; your job is to help harden and productionize them for scale — from 10 capture stations at one site to hundreds across multiple OEM plants, and from a handful of teleop stations to a multi-shift fleet. This is early, hands-on, 0-to-1 engineering: you'll ship code that runs on real hardware in real factories, and see its effect on robot behavior.
Build the field capture stack — edge software for our data collection rigs: device management, sensor orchestration, and real-time data quality monitoring that holds up on a factory floor, with workflows optimized for I/O-, compute-, and network-bound constraints
Ship the teleop stack — collection, evaluation, and operator tooling for our teleoperation stations, including metrics, task management, and the workflows our robot operators use every day
Build and contribute to integration and validation testing for field software, including hardware-in-the-loop (HIL) test setups that catch failures before they reach a live site
Build monitoring and dashboards that give visibility into fleet health, capture quality, and station uptime across sites, accounting for intermittent connectivity and bounded bandwidth in the field
Make deployment repeatable — build tooling and configuration systems that make onboarding a new manufacturing site a config change, not a custom engineering project, including device provisioning workflows
Support the field — debug issues on live systems, instrument for observability, and work directly with site operations staff and robot operators who depend on your software
2+ years of software engineering experience building production systems
Strong programming fundamentals and comfort working across the stack — edge devices, services, and local data pipelines
Experience with at least one of: edge computing, device or fleet management, real-time systems, robotics or sensor systems
Bias for ownership: you've taken features or systems from prototype to production and supported them in the field
Clear communication and close collaboration with product, research, and operations partners
Hands-on experience with sensor data (video, depth, IMU, force/torque) and the infrastructure to collect and monitor it in real time is a plus
Experience with hardware-in-the-loop or simulation-based testing (e.g., Isaac Sim, Gazebo, MuJoCo) is a plus
Background in robotics, autonomous vehicles, industrial IoT, or teleoperation systems is a plus
Exposure to manufacturing or other industrial environments is a plus