Principal AV Behavior and AI Safety Engineer
General Motors
Job Overview
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Job Description
Principal AV Behavior and AI Safety Engineer at General Motors
The Safety Assurance for Effective Autonomous Driving Software (SAFE-ADS) department is part of the Global Product Safety, System, and Certification (GPSSC) organization at GM. This department serves as the central body for automated driving system (ADS) safety, bringing together expertise to establish a comprehensive safety case. GM’s vision is zero crashes, zero emissions, and zero congestion – AV safety is paramount to achieving this vision.
The Role
The AV Safety Strategy and Assessment team is seeking a technical leader with extensive experience in the full end-to-end development lifecycle for autonomous vehicle behaviors driven by artificial intelligence & machine learning models. As the Principal AV Behavior and AI Safety Engineer, you will need to stay current on industry best practices and standards, guiding the development of GM’s AV Behavior Validation and AI safety strategy. This technical leader role requires extensive experience leading the development and implementation of AV Behavior Validation methodologies across a broad range of L4 autonomous features. A successful candidate will also have extensive experience setting the AI safety strategy for engineering development teams focused on AI/ML, and following through on implementation and validation of safe AI development and deployment practices.
If you're passionate about safety, driving innovation through AI/ML, and are a proven technical leader, this role offers an exciting opportunity to contribute to impactful projects in a dynamic team environment.
As the Principal AV Behavior and AI Safety Engineer, you will be responsible for working with our partners and customers to define safety strategies and targets for AI/ML-based autonomous driving systems. You will connect deeply to understand their challenges and needs, collaborate on new machine learning solutions, assess the safety of existing production models and cloud environments, collaborate on proof of concepts for new generative AI solutions, and provide safety guidance to a team of AI/ML developers. You will apply your experience with ISO 8800 and ISO 21448 to ensure we develop, deploy, and maintain safe AI/ML systems in simulation, on closed course, and on public roads.
What You’ll Do (Responsibilities)
- Referencing ISO 8800, ISO 21448, and AV industry best practices, develop the strategy for ensuring safe AI/ML and autonomous system development, deployment, and maintenance.
- Work with software, data science, and systems engineering teams to ensure GM safely trains new machine learning models to enable autonomous systems.
- Ensure continuity of safety as we enhance existing machine learning models to increase performance.
- Set the safety standard for how we prototype, test, and deploy new AI solutions, including Generative AI.
- Set the strategy for testing and validation of data sets and develop an assurance plan.
- Set the strategy for how we systematically break down operational design domain components and driving behavior components and how these are validated in aggregate and on a per-behavior level.
- Work with data science, systems engineering, and software teams to set the strategy for how we establish safety launch targets across vehicle behaviors and in aggregate.
- Setup an assurance process to validate launch targets have been achieved.
Your Skills & Abilities (Required Qualifications)
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
- 7+ years of experience in machine learning, engineering, data science, or a related field.
- 7+ years in autonomous vehicle or robotics development or a related field.
- Extensive experience in the following:
- Machine Learning & AI Safety: ISO 8800, ISO 21448, and other applicable industry standards and best practices for autonomous vehicles, aerospace, and/or robotics.
- Validation of AI Driven Autonomous Systems: Setting the strategy for E2E validation using techniques appropriate to validate AI models.
- 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: (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.
- Proven track record providing technical safety leadership in AI/ML and AV development.
- 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's Degree in Computer Science, Engineering, Mathematics, or related field.
- Extensive NLP solutions from business problem statement to deployment and ongoing optimization.
- 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.
- Experience leading a team of data scientists to exceed customer expectations.
Key skills/competency
- AI Safety
- Autonomous Vehicles
- Machine Learning
- ISO 8800
- ISO 21448
- Generative AI
- Deep Learning
- Python
- MLOps
- Data Validation
How to Get Hired at General Motors
- Research General Motors' culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor. Focus on their 'Zero Crashes, Zero Emissions, Zero Congestion' vision.
- Tailor your resume for AV Safety: Highlight extensive experience with ISO 8800, ISO 21448, AI/ML safety strategy, and autonomous vehicle validation methodologies to align with GM's safety-first approach.
- Prepare for technical deep dives: Be ready to discuss your expertise in Machine Learning, Generative AI, MLOps, and their application in safe autonomous system development and deployment.
- Showcase leadership and collaboration: Emphasize your proven track record in technical leadership, guiding development teams, and effective collaboration with diverse engineering and data science teams.
- Understand GM's commitment to safety: Articulate how your skills contribute to developing, deploying, and maintaining safe AI/ML systems for autonomous driving on public roads, aligning with General Motors' core mission.
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