Staff AV Behavior Safety Engineering Lead
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Job Description
Leading AI and behavior safety strategy for General Motors’ SAE Level 3–4 autonomous driving systems. Defining validation, metrics, safety cases, and launch readiness.
Responsibilities:
- Lead the strategy and support execution for defining, measuring, and validating safety of SAE Level 3–4 automated driving systems powered by machine-learned models
- Own AI and autonomous vehicle behavior safety strategy for next-generation ADS architectures
- Design and implement AI safety strategies for imitation learning and reinforcement learning models
- Own the behavior-focused portion of the ADS safety case, including claims, sufficiency criteria, and recommended evidence
- Collaborate with Software Validation, Embodied AI, Simulation, Safety Metrics, and vehicle program teams
- Define end-to-end autonomous vehicle behavior validation and AI safety methodology
- Collaborate on evaluation metrics, human benchmarks, and safety launch targets
- Develop safety performance indicators for autonomous vehicle behaviors
- Develop metrics across the machine learning model development lifecycle
- Interpret ISO/PAS 8800, ISO 21448 (SOTIF), ISO 5083, and AVSC best practices
- Assess autonomous vehicle performance using simulation, closed-course, and public-road data
- Provide prioritized feedback to engineering teams
- Define and run an assurance process to verify sufficiency criteria and safety targets for launch readiness
- Report to the AV Safety Strategy and Assurance organization and influence launch decisions for next-generation automated driving products
Requirements:
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
- 7+ years of experience in machine learning, engineering, data science, or a related field
- 7+ years of experience in autonomous vehicle or robotics development or a related field
- Experience working on production-intent autonomous vehicle programs
- Technical safety leadership in autonomous vehicle development, including safety strategies, risk assessments, validation methodologies, or safety case contributions
- Deep understanding of autonomous vehicle behavior development, including ODDs, behaviors, evaluation criteria, and analysis of simulation, closed-course, and public-road test data
- Experience with machine learning model evaluation methodologies and machine learning model development lifecycle
- Experience applying AV safety standards and best practices, including ISO/PAS 8800, ISO 5083, ISO 21448 (SOTIF), and AVSC practices
- Excellent communication and storytelling skills, including explaining complex technical tradeoffs to executives and non-technical stakeholders
- Ability to influence cross-functional teams without direct authority
- Problem-solving mindset, comfort with ambiguity, and 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: Google Cloud Platform, BigQuery, and Dataflow
- Preferred: 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%
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