Job Information
General Motors Principal AI Safety Engineer for Autonomous Vehicles: Technical Lead (GPSSC) in San Francisco, California
Job Description
Princip al AI Safety Engineer for Autonomous Vehicles : Technical L ead
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 forADSandestablishsafetyengineering guidance and sufficiency criteria.
Actively engage with partnersand seek input,provide technicalexpertiseto inform leadership decision-making,and take ownership of technical projects
Define GM’s strategy for AI safetystandards,engage externally toinfluence evolving standards, and contribute tointernal and externalthought 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 AIexpertiseand safety guidance across Global Product Safety, Systems, and Certification activities.
Identifyand 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 inAI/ML,engineeringor a related field
5+ years in autonomous vehicles,roboticsor related field
Experience in the following:
Machine Learning & AI : Extensiveexperience in buildinglarge-scalemodelswithsignificantfocus onE2Evalidation.Experience usingLarge Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM,XGBoost, Random Forest, Decision Trees, Clustering
AI S tandards and Evolving Regulations : Understanding ofISO/PAS8800,NIST AI Risk Management Framework,EU AI Act (2024-2027),otherapplicable industry standards and best practices for autonomous vehicles,aerospaceand/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
Proventrack recordproviding technicalsafetyand validationleadership in AI/MLdevelopmentand 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’sorPh.D.inComputer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience
Relevant publication
Expertisewith Large Language Models solutions from business problem statement to cloud deploymentthat have provided significant incremental business value
Experience with generative AIsolutions that you have developed and deployed into a production environmentthat 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 actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate.
• The salary range for this role is $250,600 and $384,600. The actual base salary a successful candidate will be offered within this range 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:
• 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 which 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.
#LI-KE2
This role is categorized as remote. This means the selected candidate may be based anywhere in the country of work and is not expected to report to a GM worksite unless directed by their manager.
The selected candidate will be required to travel <25% for this role.
This job may be eligible for relocation benefits.
The position is subject to export control restrictions and requires the successful candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee or refugee).
About GM
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