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Mind Robotics is building Physical AI systems for industrial deployment, focusing on dexterous robotic systems capable of adaptive, reasoning-intensive work in real-world factory environments. The company emphasizes hands-on engagement with physical systems and solving hard problems at the intersection of AI and robotics.
As a Simulation and Validation Software Engineer, you will own the test infrastructure and validation pipelines that enable firmware, controls, and runtime teams to move rapidly while maintaining reliability. Your work bridges the critical gap between simulation, hardware testing, and deployed robots in the field.
Key responsibilities include:
- Designing and building automated test suites that validate firmware, controls, and runtime behavior in software-in-the-loop (SIL) environments
- Integrating simulation environments with dynamic models and simulated sensor inputs (e.g., camera feeds) to enable development without physical hardware
- Owning regression test infrastructure, tooling for result analysis, failure triage, and coverage tracking across firmware, controls, runtime, and hardware layers
- Collaborating with firmware, controls, and runtime engineers to define testability requirements and convert real-world failures into repeatable automated test cases
- Driving validation burn-down during integration and assembly milestones, tracking issues to closure
You should have a technical degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent demonstrated exceptional ability. Strong software engineering fundamentals are essential, with fluency in Python and comfort debugging in C/C++ or Rust at the firmware level. Demonstrated experience building validation, simulation, or test infrastructure for physical systems (robots, motors, actuators) is required. You thrive with ambiguity, move fast, and possess engineering curiosity to understand how entire systems work.
Nice-to-have skills include experience with robotics middleware/runtime systems (ROS2), dynamic modeling tools (MATLAB/Simulink, MuJoCo, Gazebo), functional safety standards (IEC 61508, ISO 13849, ISO 26262), lab equipment proficiency (oscilloscopes, logic analyzers), and familiarity with agent-driven coding practices.
