Sr Manager, AV Behavior Safety Engineering (GPSSC)
$250.6k - $384.6kGeneral Motors Proving Ground
The Role The AV Safety Strategy and Assurance team is seeking a hands‑on technical senior manager 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. You will: Lead Technically 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. This includes 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 Lead People Hire, lead, and develop a high‑performing AV behavior safety engineering team. Set clear goals and expectations, provide coaching and mentorship, and grow the team’s technical depth in AV behavior safety, validation, and safety case development. Why This Role Is Unique Impact at Scale: Your work will directly influence how GM brings safe automated driving systems to millions of customers. End‑to‑End Ownership: You will own the strategy, framework, and evidence assessment for AV behavior safety. Cross‑Functional Reach: You will collaborate across AI, software, validation, simulation, metrics operations and vehicle program teams, shaping the direction of GM’s automated driving roadmap. Your Skills & Abilities (Required 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. 3+ years of people leadership experience, including hiring, leading, and growing high‑performing technical teams. What Will Give You A Competitive Edge (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, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering Cloud & Big Data Platforms : 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 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.
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