Senior Software Engineer – Autonomy Evaluation

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About the role

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 deployment at scale.     What   You’ll   Do (Responsibilities)   • Architect and implement metrics and analyses to introspect autonomous driving software performance at   subsystem   interfaces across the autonomy stack; partner closely with autonomy developers and systems engineers.   • Design and implement analysis algorithms that summarize, aggregate, and cluster metrics produced by simulations and on-road runs of the autonomy stack.   • Propose and develop new statistical and ML methods to quantify performance and   identify   patterns of system and subsystem behavior across diverse scenes and operational domains.   • Develop and apply methods to introspect the operation of ML components in the autonomy stack, including evaluation of   perception , prediction, and planning models.   • Build and   maintain   autonomy   evaluation   dashboards and interactive reports that provide clear, explainable insights (e.g., trend analysis, drift detection, scenario coverage) for development, verification, and leadership.   • Leverage vision-language models (VLMs) and large language models (LLMs), where   appropriate , to classify autonomy performance,   identify   critical scenarios, and prioritize validation efforts, integrating human-in-the-loop review where needed.   • Maintain a high technical standard through 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 subsystems.   • Strong   proficiency   developing   Python   in production team environments, including testing, performance, and code review.   • Proficiency   with   Pandas, NumPy, SciPy ,   and plotting/visualization libraries for large-scale data analysis and reporting.   • Comfort working with   C++   codebases, including r

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