The posting, in Motional's own words
archived Nov 6, 2026About the Role:
We are seeking an experienced Staff Safety Engineer to lead the definition, development, and operationalization of safety metrics and benchmarking methodologies for Level 4 autonomous vehicle (AV) and robotaxi deployment. In this role, you will establish quantitative frameworks to measure AV safety performance across on-road testing, simulation, and external benchmarks. You will develop statistically rigorous methodologies for risk estimation, counterfactual modeling, near-miss tracking, and collision severity assessment to guide deployment and software release decisions. Partnering across Safety Engineering, Systems Readiness & Performance, Autonomy, Data Science, and Fleet Operations, you will translate complex data into actionable metrics, governance frameworks, and executive evidence to ensure safe driverless commercial launch.
Safety Metrics Development:
Define, standardize, and maintain core AV safety performance indicators (SPIs), including vehicle collisions, near-misses, safety-critical interventions, traffic compliance, and surrogate safety metrics Establish standardized metric definitions, exposure denominators (e.g., VMT), data quality requirements, automated calculation pipelines, and change-management governance for safety metrics. Develop leading and lagging indicators to monitor safety performance across software releases, operational design domains (ODDs), and structured scenario taxonomies. Develop quantitative benchmarking frameworks comparing AV safety performance against human-driving baselines, counterfactual models, public datasets (e.g., SHRP2, NASS-GES), and regulatory disclosures. Evaluate comparability across operators and human drivers, accounting for exposure normalization, operating conditions, event severity levels, and reporting differences. Establish scenario-based and exposure-normalized targets that provide meaningful safety criteria and align with partner/external readiness expectations. Clearly communicate benchmarking assumptions, limitations, and statistical uncertainty. Apply statistical inference, uncertainty quantification, Bayesian methods, and risk modeling to evaluate AV behavior and scenario-level performance. Develop methods to analyze rare and high-severity events, establishing confidence intervals, sample-size requirements, and statistical evidence thresholds for release decisions. Build collision severity and injury-risk models to evaluate impact dynamics, delta-V, and potential harm mitigation. Connect quantitative findings to engineering investigations, safety mitigations, and release readiness assessments.
Read the full posting ↓
Technical Leadership:
Provide technical leadership and cross-functional alignment across Safety Case, Systems Engineering, Simulation, Data Science, and Policy teams. Lead the establishment of change management procedures and governance for approval and iteration of safety metrics and benchmarking targets. Communicate technical evidence, uncertainty, and safety readiness assessments effectively to internal executives, key partner stakeholders, and regulatory bodies.
Minimum Qualifications:
Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, Data Science, or a related technical field. 8+ years of experience in safety engineering, autonomous driving evaluation, statistical modeling, simulation-based validation, or AV risk assessment. Proven track record of defining quantitative safety metrics, SPIs, surrogate safety measures, and human benchmark models. Proficiency in Python and SQL, with experience analyzing large-scale operational or safety-related datasets. Strong expertise in statistical inference, rare-event analysis, counterfactual modeling, risk quantification, and release-readiness evaluation. Proven ability to lead cross-functional technical initiatives and communicate complex findings clearly.
Preferred Qualifications:
Master's or Ph.D. in a relevant technical or quantitative discipline. Experience with Level 4 autonomous driving, robotaxi operations, or other safety-critical systems. Experience benchmarking AV safety using public reports, regulatory disclosures, industry datasets, or published research. Familiarity with scenario taxonomies, safety case frameworks, and applicable industry standards such as UL 4600, ISO 21448 (SOTIF), ISO 8800, SAE J3237, and ISO 26262. Experience with collision severity modeling, injury-risk prediction, or human benchmark datasets #LI-LB1 The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.