[Hiring] Principal AV Behavior Safety Engineering Lead @General Motors

Role Description

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 trusted automated driving products.

As Principal AV Behavior Safety Engineering Lead, you will lead the strategy and support execution for how GM defines, measures, and validates the safety of SAE Level 3 – 4 Automated Driving Systems powered by machine-learned models. You will report into the AV Safety Strategy and Assurance organization and directly influence launch decisions for GM’s next generation of automated driving products.

If you are passionate about safety, have deep experience in autonomous vehicle development and validation, and are a proven technical leader in AI/ML-driven systems, this role is an opportunity to shape how millions of people experience safe automated driving.

The AV Safety Strategy and Assurance team is seeking a hands-on Principal engineer with extensive experience in the end-to-end development lifecycle of autonomous vehicle behaviors, from ADS Architecture, ODD and behavior definition through simulation, closed-course, and public-road validation.

You will:

• Reference and interpret standards such as ISO 21448 (SOTIF), ISO 5083, and AVSC best practices to define GM’s strategy for safe autonomous system development, validation, and deployment.
• Own safety strategy for next generation ADS architectures.
• Own the behavior-focused portion of the ADS Safety Case, including key claims, sufficiency criteria, and recommended evidence for AV behavior safety performance.
• Collaborate with Software Validation, Embodied AI, Simulation, and Safety Metrics teams to define the end-to-end AV behavior validation methodology for AI-driven systems.
• Set the strategy for how we systematically break down ODDs and how performance is validated per behavior and in aggregate.
• Collaborate on evaluation metrics, human benchmarks, and safety launch targets for AV behaviors and overall system performance, including supporting development of safety performance indicators (SPIs) for AV behaviors.
• Assess AV performance across safety and reliability dimensions using simulation, closed-course, and public-road data and provide clear, prioritized feedback to engineering teams.
• Define and run an assurance process to verify the sufficiency criteria and safety targets to support launch readiness.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
• 8+ years of experience in machine learning, engineering, data science, or a related field.
• 8+ years in autonomous vehicle or robotics development or related field.
• Demonstrated experience working on production-intent AV programs.
• Track record providing technical safety leadership in AV development (e.g., defining safety strategies, risk assessments, validation methodologies, safety case contributions).
• Deep understanding of AV behavior development: defining ODDs, behaviors, and evaluation criteria; analyzing simulation, closed-course, and public-road test data; and generating prioritized, actionable recommendations for developers.
• Experience applying AV safety standards and best practices, such as ISO 5083, ISO 21448 (SOTIF), and AVSC practices.
• Excellent communication and storytelling skills, including the ability to explain complex technical tradeoffs to executives and non-technical stakeholders.
• Proven ability to influence cross-functional teams (Software, AI/ML, Systems Engineering, Product, Program Management, Operations) without direct authority.
• Strong problem-solving mindset, comfort with ambiguity, and a proactive attitude toward learning and continuous improvement.

Requirements

• Masters Degree in Computer Science, Engineering, Mathematics or related field (Preferred).
• Programming & Frameworks: Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL.
• Machine Learning & AI: Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering.
• Cloud & Big Data Platforms: Microsoft Azure (Data Lake, Machine Learning, Databricks) (Preferred).
• 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.

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.
• Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate.