Principal AI Safety Engineer for Autonomous Vehicles: Technical Lead (GPSSC)

Principal AISafety Engineer for Autonomous Vehicles: Technical Lead The Safety Assurance for Effective Autonomous Driving Software (SAFE‑ADS) department is part of GM’s Global Product Safety, System, and Certification (GPSSC) organization. Our mission is to help GM deliver trustworthy automated‑driving products. As the central authority for automated driving system (ADS) safety, SAFE‑ADS brings together experts from across the company to develop and maintain a comprehensive safety case including safety performance indicators for GM’s automated‑driving technologies. GM’s vision is zero crashes, zero emissions, and zero congestion—and autonomous vehicle safety is essential to achieving that vision. The Role The AV Safety Strategy and Assessment team is seeking an AI Safety Technical Leader with deep experience across the full end‑to‑end development lifecycle of automated driving system (ADS) technology driven by artificial intelligence and machine learning models. As the AI Safety Principal Engineer, you will stay current on industry best practices and standards while guiding the development of GM’s AI safety strategy for autonomous vehicles (AV). This role requires significant experience driving the technology development and validation of AI models for safety‑critical applications. The ideal candidate will bring strong AI domain expertise across safety engineering, data lifecycle management, model development, verification and validation, frameworks and tools, and operational assurance. If you’re passionate about autonomous vehicle technology, committed to advancing safety through innovation, and are a proven technical leader, this role offers an exciting opportunity to make a meaningful impact on the future of transportation safety in a dynamic and fun environment. As the AI Safety Principal Engineer for AV, you will work closely with cross‑functional partners and customers to define safety strategies and sufficiency criteria for AI/ML‑based ADS features. You will engage deeply with stakeholders to understand their challenges and needs, collaborate on new AI/ML solutions, and evaluate the safety of models and cloud environments to support safety‑critical applications. In this role, you will also provide safety guidance to a team of AI/ML developers and system engineers. Leveraging your experience with industry standards such as ISO/PAS 8800, you will champion GM’s AI safety case framework and help ensure the safe deployment of AI‑enabled ADS technologies. What You’ll Do (Responsibilities) Lead the development of AI safety strategies for ADS and establish safety engineering guidance and sufficiency criteria. Actively engage with partners and seek input, provide technical expertise to inform leadership decision‑making, and take ownership of technical projects. Define GM’s strategy for AI safety standards, engage externally to influence evolving standards, and contribute to internal and external thought leadership that strengthens GM’s position in the autonomous vehicle ecosystem. Support regulatory rulemaking and policy responses related to AI safety‑critical systems. Establish an assurance plan and process to evaluate AI‑related safety case evidence and verify that sufficiency criteria are met. Provide AI expertise and safety guidance across Global Product Safety, Systems, and Certification activities. Identify and drive opportunities to improve the efficiency and quality of safety work through the application of AI methodologies. Mentor and develop team members, fostering a culture of technical excellence and continuous learning. Your Skills & Abilities (Required Qualifications) Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience. 10+ years of experience in AI/ML, engineering or a related field. 5+ years in autonomous vehicles, robotics or related field. Experience in the following: Machine Learning & AI : Extensive experience in building large‑scale models with significant focus on end‑to‑end validation. Experience using Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering. AI Standards and Evolving Regulations : Understanding of ISO/PAS 8800, NIST AI Risk Management Framework, EU AI Act (2024‑2027), other applicable industry standards and best practices for autonomous vehicles, aerospace and/or robotics. Programming & Frameworks : Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit‑learn, LangChain, SQL. Cloud & Big Data Platforms (Preferred): Microsoft Azure‑Data Lake, Machine Learning, Databricks. (Nice to Have): AWS‑S3, SageMaker, Bedrock, or Google Cloud Platform (BigQuery, Dataflow, AI Platform). Deployment & MLOps : MLflow, Model Monitoring & Versioning, Docker & Kubernetes, GitHub, Jira. Data Analysis & Visualization : Tableau, PowerBI, Pandas, NumPy. Proven track record providing technical safety and validation leadership in AI/ML development and deployment. Excellent communication and collaboration skills, with the ability to work effectively in a team environment. Strong problem‑solving mindset and a proactive attitude towards learning and self‑improvement. What Will Give You a Competitive Edge (Preferred Qualifications) Master’s or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience. Relevant publication. Expertise with Large Language Models solutions from business problem statement to cloud deployment that have provided significant incremental business value. Experience with generative AI solutions that you have developed and deployed into a production environment that have provided significant incremental business value. Compensation The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The salary range for this role is $250,600 to $384,600. The actual base salary a successful candidate will be offered will vary based on factors relevant to the position. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. Company vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, though you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies. #J-18808-Ljbffr General Motors