Instrument Engineering, Senior

Engineering · Ann Arbor, MI - Hybrid · Senior level

A strong candidate has three to five years on real robotic or autonomous systems, solid C and Python, and comfort with CI pipelines and git workflows in a large codebase. The work calls for judgment about what to test first and steady coordination across perception, planning, and controls groups.

The company's driving stack is built on reinforcement learning, so integration work means validating learned behavior across many scenarios, not just checking fixed rules. Simulation campaigns and automated pipelines do more of the repetitive checking, which frees the engineer to judge edge cases, diagnose regressions, and decide what deserves a real world test. Human judgment stays central in setting priorities and explaining system health to others.

The role builds hands on skill with simulation based validation and automated testing of learned driving policies, which is close to how modern autonomy teams work. A candidate can prepare by practicing scenario design, regression tracking, and metrics reporting on any robotics project, and by learning how reinforcement learning policies are evaluated before road testing. Experience with an AV simulation platform helps.

AV or robotics integration testing

C and Python programming

CI/CD and automated test pipelines

A self-driving vehicle company whose AI, trained through reinforcement learning rather than only pre-collected data, already carries riders in Atlanta, Minnesota and Japan.

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