Job Description
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.
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
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
Your work will define how collision outcomes and severity are modeled and evaluated, directly influencing safety strategy, performance benchmarks, and product decision making.
GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.
This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.
#LI-SA2
GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as remote. This means the selected candidate may be based anywhere in the country of work and is not expected to report to a GM worksite unless directed by their manager. The selected candidate will be required to travel <25% for this role. This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.About GM
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