Principal Engineer Team Lead, Behavior Safety & Metrics

Accountabilities:: Serve as the technical authority for evaluation across Behavior teams, connecting model-level development with overall autonomous driving system performance. Define and lead evaluation strategies for prediction and planning models, including open-loop and simulation-based assessments. Design and implement advanced performance metrics, including machine learning-based approaches to measure model impact on end-to-end system behavior. Incorporate counterfactual reasoning and reaction-time analysis into evaluation frameworks to better understand system decisions and outcomes. Develop data mining strategies and assess the coverage, quality, and representativeness of training and evaluation datasets across prediction and planning. Build scalable evaluation tools, pipelines, and processes, identifying gaps and collaborating with machine learning engineers and roboticists to address complex technical challenges. Establish performance targets and acceptance criteria across safety, comfort, and driving assertiveness, supported by rigorous analysis and evidence. Work closely with Safety, Infrastructure, Operations, Legal, and other Systems teams to guide design improvements and assess the impact of new capabilities. Ensure that system changes deliver measurable improvements and meet the required launch criteria for safe and effective autonomous driving. Requirements: Bachelor's degree in Computer Science, Systems Engineering, Robotics, or a related technical field, with at least 7 years of relevant experience; alternatively, a master's degree or PhD with at least 5 years of experience. Strong foundation in probability, statistics, data science, and scientific methods applied to complex multi-agent systems. Proficiency in Python, SQL, and production-level data analysis, including statistical analysis and visualization. Experience defining performance targets and acceptance criteria for safety, comfort, and assertiveness, and producing evidence to support technical decisions. Demonstrated ability to solve complex, cross-disciplinary engineering problems and develop innovative, maintainable solutions. Proven experience leading technical initiatives, aligning stakeholders, and driving projects through the development process. Working knowledge of hazard and safety analysis methods, such as STPA, HAZOP, FMEA, and hazard analysis and risk assessment. Strong communication skills, with the ability to explain complex technical concepts to engineering teams, cross-functional partners, and executive stakeholders. Preferred experience applying statistical and machine learning methods to quantify performance, detect regressions, and identify behavioral patterns at scale. Deep experience in autonomous robotics prediction and/or planning, including evaluation of machine learning-based systems in production environments. Familiarity with public autonomous vehicle datasets and benchmarks, such as Waymo Open Dataset and nuScenes, as well as industry metrics for trajectory forecasting and motion planning. Experience building or using large-scale data pipelines. Familiarity with SOTIF, ISO 26262, UL 4600, AVSC behavior competencies, and other relevant industry standards is an advantage. Benefits: Base salary: $240,000–$330,000 USD. Potential additional compensation through bonuses and/or company equity. Medical, dental, and vision insurance. 401(k) retirement plan with company match. Health Savings Accounts (HSA). Life insurance. Pet insurance. Additional employee benefits and support programs, depending on eligibility.