Staff AV Behavior Safety Engineering Lead

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

📋 Description

• Lead the strategy and support the implementation for defining, measuring, and validating the safety of SAE Level 3–4 automated driving systems driven by machine-learned models.

• Take ownership of the AI and autonomous vehicle behavior safety strategy for next-generation ADS architectures.

• Design and execute AI safety strategies for imitation learning and reinforcement learning models.

• Manage the behavior-focused segment of the ADS safety case, encompassing claims, sufficiency criteria, and recommended evidence.

• Collaborate with Software Validation, Embodied AI, Simulation, Safety Metrics, and vehicle program teams.

• Define the end-to-end validation methodology for autonomous vehicle behavior and AI safety.

• Work together on evaluation metrics, human benchmarks, and safety launch targets.

• Develop safety performance indicators for autonomous vehicle behaviors.

• Establish metrics throughout the machine learning model development lifecycle.

• Interpret ISO/PAS 8800, ISO 21448 (SOTIF), ISO 5083, and AVSC best practices.

• Evaluate autonomous vehicle performance using simulation, closed-course testing, and public-road data.

• Provide prioritized feedback to engineering teams.

• Define and execute an assurance process to verify sufficiency criteria and safety targets for launch readiness.

• Report to the AV Safety Strategy and Assurance organization and impact launch decisions for next-generation automated driving products.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.

• Over 7 years of experience in machine learning, engineering, data science, or a similar discipline.

• More than 7 years of experience in autonomous vehicle or robotics development or a related area.

• Experience with production-intent autonomous vehicle programs.

• Demonstrated technical safety leadership in autonomous vehicle development, including safety strategies, risk assessments, validation methodologies, or contributions to safety cases.

• Profound understanding of autonomous vehicle behavior development, covering ODDs, behaviors, evaluation criteria, and analysis of simulation, closed-course, and public-road test data.

• Familiarity with methodologies for evaluating machine learning models and the machine learning model development lifecycle.

• Experience applying AV safety standards and best practices, such as ISO/PAS 8800, ISO 5083, ISO 21448 (SOTIF), and AVSC practices.

• Strong communication and storytelling abilities, including the capacity to explain complex technical trade-offs to executives and non-technical stakeholders.

• Ability to influence cross-functional teams without direct authority.

• Problem-solving mindset, comfort with ambiguity, and a proactive approach to learning and continuous improvement.

• Preferred: Master's degree in Computer Science, Engineering, Mathematics, or a related field.

• Preferred: Experience with LLMs, Generative AI, deep learning, imitation learning, and reinforcement learning.

• Preferred: Familiarity with Google Cloud Platform, BigQuery, and Dataflow.

• Preferred: Experience with MLflow, model monitoring and versioning, GitHub, and Jira.

🏝️ Benefits

• Bonus potential through an incentive pay program based on company performance, job level, and individual performance.

• Medical, dental, and vision benefits.

• Health Savings Account.

• Flexible Spending Accounts.

• Retirement savings plan.

• Sickness and accident benefits.

• Life insurance.

• Paid vacation and holidays.

• Tuition assistance programs.

• Employee assistance program.

• GM vehicle discounts.

• Company vehicle evaluation program, subject to motor vehicle report review.

• Remote work arrangement.

• Travel under 25%.