AV Safety Engineering Analytics AI/ML Engineer (GPSSC)

General Motors

19h • Remote

About The Position

The AV Safety Engineering Analytics team is seeking an AI/ML Engineer with capabilities at the intersection of vehicle engineering, AI/ML and cloud processing. This team supports various departments by providing data and analytics for AV safety decision-making. They integrate data from vehicle systems, company databases, third-party services, federal agencies, and state DOTs to inform system design and quantify driving performance. The role involves continuous up-time proactive analyses and supporting specific investigations. The ideal candidate is passionate about autonomous vehicle technology, advancing safety through AI/ML, and transforming big data into clear guidance.

Requirements

• Master’s degree in Computer Science, Mechanical Engineering, Vehicle Engineering, Physics, or a related field; or equivalent practical experience focused on AI/ML
• 10+ years of experience in large scale analyses of vehicle related data
• 5+ years in safety-critical AI/ML systems in automotive engineering applications
• Experience in Machine Learning & AI: Extensive experience in building large-scale models with significant focus on E2E validation. Experience using Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering
• Experience in AI Standards and Evolving Regulations: Understanding of ISO/PAS 8800, NIST AI Risk Management Framework, EU AI Act (2024-2027), other applicable industry standards and best practices for autonomous vehicles, aerospace and/or robotics.
• Experience in Programming & Frameworks: Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL
• Experience in Cloud & Big Data: Experience in cloud-based large scale process including notifications, queuing, serverless cloud functions, event driven processing, code as infrastructure, containerization, process monitoring, process optimization, identity and access management, service to service access, etc. (Microsoft Azure - Data Lake, Machine Learning, Databricks), (AWS - S3, SageMaker, Bedrock) or Google Cloud Platform (BigQuery, Dataflow, AI Platform)
• Experience in Deployment & MLOps: CI/CD, MLflow, Model Monitoring & Versioning, Docker & Kubernetes, GitHub, Jira, Jenkins, Poetry, Terraform
• Experience in Data Analysis & Visualization: Tableau, PowerBI, Plotly/Dash, Shiny, Pandas, NumPy
• Proven track record providing technical leadership in AI/ML applied to safety-critical systems
• 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

Nice To Haves

• Record of involvement in public AI/ML related discourse through conference participation or publications.
• Experience productionizing the use of AI/ML within the corporate setting.

Responsibilities

• Contribute to the development of data analytics infrastructure that supports safety assurance analytics addressing internal and external stakeholder needs across the phases of automated vehicle development and deployment, including both real-world and simulation data.
• Apply AI/ML expertise to developing trustworthy and explainable methods for validating the safety performance of an AI/ML based automated driving system.
• Mentor and develop team members in the appropriate implementation of AI/ML to support the mission of the SAFE-ADS department and AV Safety Engineering Analytics team.
• Pilot and develop metrics for monitoring of development operations and deployment, and establish sufficiency criteria for launch readiness.
• Develop methods for leveraging a variety of internal and external data sources for AI/ML based safety monitoring and contribute to the development of a reliable supply chain of continuously flowing data from a variety of sources (internal and external) to support safety assurance related activities.
• Implement cloud-based continuous up-time analytics solutions for monitoring driving performance for safety and generating browser based interactive visualizations and periodic reporting artifacts.
• Actively contribute to determining appropriate use of AI/ML approaches within automated driving systems and provide technical expertise to inform leadership decision-making regarding mechanisms for ensuring they are trustworthy and explainable.
• Through AI/ML expertise, contribute to the definition of GM’s data sourcing and processing strategy for AV safety assurance needs, engage externally to influence evolving standards, and contribute to internal and external thought leadership that strengthens GM’s position in the autonomous vehicle ecosystem.
• Represent SAFE-ADS in AI/ML related discussions across Global Product Safety, Systems, and Certification activities.
• Identify and drive opportunities to improve the efficiency, quality and transparency of safety analytics within GPSSC and across GM.

Benefits

• Company Vehicle: 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.
• Total Rewards resources

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees