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Mind Robotics is building robots that learn from real-world experience. As a Software Engineer on the Edge & Field Systems team, you'll be a founding engineer responsible for hardening and productionizing the field data collection and teleoperation systems that power the company's robot training pipeline.
You'll own the application layer that runs on edge devices deployed across manufacturing sites. Your work spans the full stack: building the field capture stack for data collection rigs (device management, sensor orchestration, real-time data quality monitoring), shipping the teleoperation stack for operator tooling and task management, and creating the infrastructure to scale from 10 capture stations at one site to hundreds across multiple OEM plants.
Key responsibilities include: developing edge software that handles I/O, compute, and network constraints on factory floors; building monitoring and dashboards for fleet health and capture quality across distributed sites with intermittent connectivity; creating repeatable deployment and device provisioning workflows so onboarding new manufacturing sites becomes a configuration change; implementing hardware-in-the-loop testing to catch failures before production; and supporting live systems by debugging issues and working directly with site operations and robot operators.
You'll ship code that runs on real hardware in real factories and directly see its impact on robot behavior. This is early-stage, hands-on 0-to-1 engineering with direct ownership from prototype to production support.
Requirements: 2+ years building production systems; strong programming fundamentals across edge devices, services, and data pipelines; experience with edge computing, device/fleet management, real-time systems, robotics, or sensor systems; proven track record taking features from prototype to production and supporting them in the field; clear communication and collaboration skills.
Plus factors: hands-on experience with sensor data (video, depth, IMU, force/torque) and real-time collection infrastructure; hardware-in-the-loop or simulation testing (Isaac Sim, Gazebo, MuJoCo); robotics, autonomous vehicles, industrial IoT, or teleoperation background; manufacturing or industrial environment exposure.
