Staff Safety Engineer, Safety Metrics and Benchmarking

This is a fully remote position, open to applicants in Nevada.

📋 Description

• Oversee the formulation, development, and implementation of safety metrics and benchmarking techniques for Level 4 autonomous vehicle and robotaxi deployment.

• Create quantitative frameworks to evaluate AV safety performance through on-road testing, simulation, and external benchmarks.

• Formulate methodologies for risk estimation, counterfactual modeling, near-miss tracking, and collision severity evaluation.

• Define and uphold AV safety performance indicators, which encompass collisions, near-misses, safety-critical interventions, traffic compliance, and surrogate safety metrics.

• Set metric definitions, exposure denominators, data quality standards, automated calculation processes, and change-management governance.

• Develop leading and lagging indicators across software releases, operational design domains, and scenario classifications.

• Establish benchmarking frameworks that compare AV safety against human-driving baselines, counterfactual models, public datasets, and regulatory disclosures.

• Utilize statistical inference, uncertainty quantification, Bayesian methods, and risk modeling techniques.

• Examine rare and high-severity incidents and determine confidence intervals, sample-size requirements, and statistical evidence thresholds.

• Create collision severity and injury-risk models.

• Relate quantitative findings to engineering investigations, safety mitigations, and release-readiness evaluations.

• Offer technical leadership and foster cross-functional collaboration across Safety Case, Systems Engineering, Simulation, Data Science, and Policy teams.

• Convey technical evidence, uncertainty, and safety readiness evaluations to executives, partners, and regulatory bodies.

⛳️ Requirements

• 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.

• Demonstrated success in defining quantitative safety metrics, SPIs, surrogate safety measures, and human benchmark models.

• Proficient in Python and SQL, with experience in analyzing large-scale operational or safety-related datasets.

• Strong knowledge of statistical inference, rare-event analysis, counterfactual modeling, risk quantification, and release-readiness evaluation.

• Proven capability to lead cross-functional technical projects and clearly communicate complex findings.

• Master's or Ph.D. in a relevant technical or quantitative discipline (preferred).

• Experience with Level 4 autonomous driving, robotaxi operations, or other safety-critical systems (preferred).

• Familiarity with benchmarking AV safety using public reports, regulatory disclosures, industry datasets, or published research (preferred).

• Understanding of scenario taxonomies, safety case frameworks, and standards such as UL 4600, ISO 21448 (SOTIF), ISO 8800, SAE J3237, and ISO 26262 (preferred).

• Background in collision severity modeling, injury-risk prediction, or human benchmark datasets (preferred).

🏝️ Benefits

• Medical insurance

• Dental insurance

• Vision insurance

• 401(k) with a company match

• Health savings accounts

• Life insurance

• Pet insurance

• Potential bonus compensation

• Potential company equity

• Equal employment opportunity and inclusive work environment