Safety Modeling Engineer – Collision Severity and Safety Impact Modeling (GPSSC)

General Motors is seeking a Safety Modeling Engineer to lead the development of collision outcome and severity modeling methods for automated driving systems. The role involves designing models to quantify safety performance and applying statistical and machine learning methods to large-scale datasets.

Responsibilities:

• Develop counterfactual models to estimate collision outcomes under different system and driver responses
• Build statistical, machine learning, and physics-informed models to estimate collision severity and risk
• Analyze large-scale driving and simulation datasets to generate severity metrics and safety benchmarks
• Build scalable modeling pipelines and data workflows
• Partner with cross-functional teams to translate modeling results into safety evaluation methodologies and decision-making
• Contribute to safety case evidence related to collision risk and severity

Requirements:

• Bachelor's or higher degree in Engineering, Data Science, Applied Mathematics, Physics, Computer Science, or related field
• Expertise in vehicle safety, safety impact assessment, injury risk assessment, safe system approaches, scenario-based testing, biomechanics, collision modeling, injury scales or related fields
• Strong proficiency in Python and SQL and data visualization
• Dev Ops and Infrastructure as Code: CI/CD, versioning, Docker & Kubernetes, GitHub, Jira, Jenkins, Poetry, Terraform
• Experience developing statistical or machine learning models using large datasets
• Experience with simulation-based analysis, safety analytics, or risk modeling
• Demonstrated ability to tackle technical challenges and propose maintainable solutions
• Strong analytical and problem-solving skills
• Ability to communicate technical results to cross-functional stakeholders
• Master's or Ph.D. in a relevant technical field
• Relevant publication
• Experience with collision analysis, injury risk modeling, or crash reconstruction
• Experience with causal inference or counterfactual modeling techniques
• Familiarity with simulation-based evaluation or scenario analysis
• Experience working with cloud or distributed data platforms