Senior Software Engineer, Autonomy Evaluation

Job Description General Motors is a global leader in advanced driver assistance. With Super Cruise hands-free technology in more than 500,000 Super Cruise–equipped vehicles on the road and over 700 million hands-free miles driven, GM is proving that automation can be trusted, intuitive, and helpful. GM has the global reach to bring cutting-edge advances to everyday drivers at unprecedented scale. Join us to help deliver the next generation of safe and delightful personal autonomous vehicle experiences. About the Organization The Evaluation team builds and evolves the evaluation ecosystem that powers the development and scaling of GM’s autonomous driving technology. We develop metrics, automated workflows, and analysis approaches that enable data-driven decisions across AV development and verification. Partnering with Autonomy, Simulation, Systems, and Safety teams, we act as system-level integrators and arbiters of end-to-end AV quality. We own large-scale test scenario libraries, continuous evaluation pipelines, and critical risk assessment and release-gating components, treating road testing, data mining, training, and metrics as first-class use cases in a unified analytics framework. By joining this team, you will help shape GM’s core evaluation platforms, turn system-level results into clear feedback for engineering and leadership, and help accelerate validated AV deplo [... source excerpt omitted ...] h thoughtful system design, code reviews, testing, observability, and adherence to software-engineering best practices. Interface with cross-organizational partners to articulate requirements, resolve handoff issues, and share best practices around evaluation, metrics, and experiment design. Your Skills & Abilities (Required Qualifications) 5+ years of applied experience with robotics or autonomous systems software (e.g., sensors, perception, prediction, planning, or control), data analysis, ML evaluation, or autonomy analytics. 3+ years evaluating dynamic systems using numerical and/or ML approaches, including time-series data, state derivatives, dynamics, and interconnected sub [... source excerpt omitted ...] tics, Mechanical or Aerospace Engineering, Machine Learning, Data Science, or a related field, or equivalent practical experience What Will Give You a Competitive Edge (Preferred Qualifications) Experience in autonomous driving or field robotics, including visualizing and interpreting results from simulation and field experiments. Experience evaluating robotics or AV systems using sensor data (e.g., camera, lidar, radar) and large-scale time-series analysis. Strong intuition for data visualization and the ability to decompose high-dimensional metrics into clear, trustworthy, and consumable views for technical and non-technical audiences. Familiarity with statistical modeling, expe