Sr Staff AV Safety Engineer
Job Summary
The Sr Staff AV Behavior Safety Engineer will lead the strategy for defining, measuring, and validating the safety of SAE Level 3-4 Automated Driving Systems. This role involves developing safety cases, defining validation methodologies for AI-driven systems, and providing actionable feedback based on simulation and real-world data. The position requires deep expertise in autonomous vehicle development and a strong ability to influence cross-functional technical teams.
Responsibilities
- Define safety strategy and validate SAE Level 3-4 AV systems
- Develop and maintain the ADS Safety Case and SPIs
- Design end-to-end AV behavior validation methodologies
- Analyze simulation and real-world test data to provide engineering feedback
- Collaborate across AI, software, and validation teams
Required Skills
- Autonomous vehicle development (6+ years)
- Machine learning and AI systems expertise
- ISO 21448 (SOTIF) and ISO 5083 standards
- Technical leadership and cross-functional influence
- Data analysis and simulation validation
Job Details
### The Role
The AV Behavior Safety Engineering team is seeking a hands-on engineer with extensive experience in the end-to-end development lifecycle of autonomous vehicle behaviors, from ODD and behavior definition through simulation, closed-course, and public-road validation.
### Responsibilities
- 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 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 development of safety performance indicators (SPIs).
- 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.
### Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
- 6+ years of experience in machine learning, engineering, data science, or a related field.
- 6+ 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.
- Deep understanding of AV behavior development: defining ODDs, behaviors, and evaluation criteria; analyzing simulation, closed-course, and public-road test data.
- Experience applying AV safety standards and best practices, such as ISO 5083, ISO 21448 (SOTIF), and AVSC practices.
- Excellent communication skills and proven ability to influence cross-functional teams.
### Preferred Qualifications
- Masters Degree in Computer Science, Engineering, Mathematics or related field.
- 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, NLP, SVM, XGBoost, Random Forest, Decision Trees, Clustering.
- Cloud & Big Data Platforms: Microsoft Azure (Data Lake, Machine Learning, Databricks), 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.