Senior Software Systems Engineer, Autonomous Systems Validation Confidence

Job description

Job responsibilities

• Develop scalable frameworks and methods for measuring validation confidence across simulation and real-world testing, including coverage, sampling, metric quality, statistical significance, and regression detection.
• Build tools and data pipelines for test execution, analysis, metric computation, scorecards, and confidence reporting.
• Evaluate simulation validity and road predictive power using measurable, defensible criteria; analyze test and vehicle data to identify uncertainty, pipeline issues, regressions, and gaps in evidence.
• Translate validation claims and release questions into requirements, experiments, test suites, metrics, and quantitative decision criteria.
• Improve the throughput, repeatability, and quality of validation workflows.
• Partner with simulation, safety, autonomy, and release teams, and communicate conclusions, assumptions, limitations, and recommendations clearly.

Job requirements

• Strong programming skills in Python, C++, or a comparable language, with experience writing clear, testable, maintainable code.
• Experience applying engineering or quantitative methods to a physical, cyber-physical, or other real-world system.
• Ability to turn ambiguous validation questions into measurable requirements, metrics, experiments, or decision criteria, and investigate complex behavior using incomplete or noisy data.
• Ability to collaborate across disciplines and explain technical results with appropriate precision and context.
• Bachelor’s degree in engineering, physics, applied mathematics, statistics, data science, or a related technical field, or equivalent practical experience.
• Experience with autonomous vehicles, robotics, simulation, aerospace, industrial automation, or another safety-relevant engineered system.
• Experience with verification and validation, test automation, scenario generation, requirements-based testing, or performance benchmarking.
• Experience designing coverage measures, scorecards, confidence metrics, or regression-detection methods.