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

General Motors

1d • Remote

About The Position

Work arrangement: Remote: This role is based remotely but if you live within a 50-mile radius of [Atlanta, Austin, Detroit, Warren, Milford or Mountain View], you are expected to report to that location three times per week, at minimum. The AV Safety Engineering Analytics team is building the next generation of quantitative safety modeling capabilities for automated driving systems. We are seeking a Safety Modeling Engineer to lead development of counterfactual collision outcome and severity modeling methods that enable rigorous measurement of ADS performance. The Role In this role you will integrate domain expertise to design and build models that answer foundational questions such as: How would collision outcomes change under different response strategies? How do we quantify severity and risk across diverse real-world scenarios? What constitutes defensible safety performance benchmarks? You will apply statistical, machine learning, and physics-informed methods to large-scale real and simulated driving datasets and embed these models into scalable evaluation pipelines supporting safety assessment and safety case evidence. This role requires strong analytical depth, methodological rigor, and practical judgment. You will help shape how collision outcomes and severity are quantified across ADS programs.

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

Nice To Haves

• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level