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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.
Job Responsibility:
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.
Requirements:
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 Machine Learning & AI: Extensive experience in building large-scale models with significant focus on E2E 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.
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
Nice to have:
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
Cloud & Big Data Platforms: ( Nice to Have (AWS - S3, SageMaker, Bedrock) or Google Cloud Platform (BigQuery, Dataflow, AI Platform))