Senior Software Engineer – Autonomy Evaluation
General MotorsResponsibilities
- Architect and implement metrics and analyses for autonomous-driving software performance across subsystem interfaces.
- Design analysis algorithms to summarize, aggregate, and cluster simulation and on-road autonomy results.
- Develop statistical and ML methods for measuring performance and identifying system and subsystem behavior patterns.
- Evaluate perception, prediction, and planning models within the autonomy stack.
- Build and maintain evaluation dashboards and interactive reports covering trends, drift detection, and scenario coverage.
- Use vision-language models and large language models when appropriate to classify performance, identify critical scenarios, and prioritize validation with human review.
- Maintain production-quality software through system design, code reviews, testing, and observability.
- Drive cross-organizational requirements, resolve handoff issues, and share evaluation and experiment-design practices.
Requirements
- 5+ years of applied experience with robotics or autonomous-systems software, data analysis, ML evaluation, or autonomy analytics.
- 3+ years evaluating dynamic systems using numerical or ML approaches involving time-series data, dynamics, state derivatives, and interconnected subsystems.
- Strong production Python development experience, including testing, performance, and code review.
- Proficiency with Pandas, NumPy, SciPy, and plotting or visualization libraries for large-scale analysis and reporting.
- Comfort working with C++ codebases, including reading, debugging, and instrumenting algorithms.
- Demonstrated technical leadership in architectural decisions, cross-team design influence, and end-to-end ownership of complex features or services.
- Bachelor’s, master’s, or PhD in computer science, robotics, mechanical or aerospace engineering, machine learning, data science, or a related field, or equivalent practical experience.
- Preferred experience includes autonomous driving or field robotics, sensor-data analysis, simulation and field experiments, statistical modeling, experimental design, hypothesis testing, SQL, ROS, log pipelines, evaluation platforms, computational geometry, linear algebra, PyTorch, and ML techniques for autonomy.
- Preferred candidates may have experience with agent interaction modeling, release-gating and safety decisions, and AI-assisted development or analytics tools.
Benefits
- GM provides employee well-being and career-support benefits through its Total Rewards resources.
- Applicants may be required to complete a role-related assessment and/or pre-employment screening.
About General Motors
General Motors’ vision is to create a world with Zero Crashes, Zero Emissions and Zero Congestion, and we have committed ourselves to leading the way toward this future. Today, we are in the midst of a transportation revolution, and we have the ambition, the talent and the technology to realize the safer, better and more sustainable world we want. As an open, inclusive company, we’re also creating an environment where everyone feels welcomed and valued for who they are. One team, where all ideas are considered and heard, where everyone can contribute to their fullest potential, with a culture based in respect, integrity, accountability and equality. Our team brings wide-ranging perspectives and experiences to solving the complex transportation challenges of today and tomorrow. For information on the GM Privacy Statement, please visit http://www.gm.com/privacy-statement.html