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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 an unprecedented scale. Join us to help deliver the next generation of safe and delightful personal autonomous vehicle experiences.
Job Responsibility:
Design, build, and maintain large-scale test infrastructure and evaluation pipelines that enable and quantify the accuracy, reliability, and efficiency of simulation tests used for autonomous vehicle software validation.
Develop and maintain GM's core simulation dashboards and reports, delivering clear, actionable, and interpretable insights on test operations, simulation trust and health trends to engineering teams and leadership.
Drive scalable simulation quality assessments, standardized processes, and automation to support seamless integration of automated outputs with human-in-the-loop analysis and evaluation.
Collaborate with cross-functional partners across Autonomy, Systems, Safety, and customer teams to define, refine, and drive consensus on simulation validation methodologies and requirements.
Uphold high standards for code quality and software architecture through code reviews and technical leadership, mentoring other engineers on software engineering and simulation testing best practices.
Leverage AI-assisted development tools and analytics platforms to enhance productivity, improve code quality, and drive innovation in simulation testing.
Requirements:
5+ years of applied experience developing complex evaluation, simulation, or test frameworks.
Proficient in developing Python for production systems, including unit testing, code review, performance tradeoffs, and reliability best practices.
Demonstrated ability to drive technical design and execution across multiple teams and organizations in a remote or distributed environment.
Strong communication and collaboration skills.
BS, MS, or PhD in Computer Science, Engineering, or equivalent experience.
Nice to have:
Experience testing and evaluating robotics systems or autonomous vehicles, including working on simulation frameworks.
Experience working on test strategies and validation for safety-critical products.
A strong, data-driven curiosity to investigate anomalies and systematically root-cause discrepancies.
Familiarity with SQL, time-series data analysis, performance monitoring tools and dashboarding systems (e.g., Looker, Streamlit).