AV Safety Engineering Analytics AI/ML Engineer (GPSSC)

Job Overview Work arrangement: Remote. The role is based remotely but if you live within a 50‑mile radius of Atlanta, Austin, Detroit, Warren, Milford, or Mountain View, you are expected to report to that location three times per week, at minimum. About the Role The AV Safety Engineering Analytics team is seeking an AI/ML Engineer with expertise at the intersection of vehicle engineering, AI/ML, and cloud processing. The team supports stakeholders across the company by integrating continuously flowing data from vehicle systems, company databases, third‑party services, federal agencies, and state DOTs to inform system design and quantify driving performance. The focus is on continuous up‑time proactive analyses as well as supporting specific investigations. The role offers opportunities to make a meaningful impact on the future of transportation safety. Key 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 develop 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 to support safety assurance 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. Required Experience & Skills 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. Extensive experience in building large‑scale models with significant focus on end‑to‑end validation, including LLMs, generative AI, RAG, deep learning, reinforcement learning, NLP, SVM, XGBoost, random forest, decision trees, clustering. Understanding of AI standards and evolving regulations such as ISO/PAS 8800, NIST AI Risk Management Framework, EU AI Act (2024‑2027), and other applicable industry standards for autonomous vehicles. Proficiency in Python, R, Java, PySpark, PyTorch, TensorFlow, scikit‑learn, LangChain, SQL. Experience with cloud Big Data platforms (Microsoft Azure, AWS, or Google Cloud) and related services such as data lake, machine learning, databricks, S3, SageMaker, Bedrock, BigQuery, Dataflow, AI Platform. Proficiency in MLOps tooling: CI/CD, MLflow, model monitoring & versioning, Docker, Kubernetes, GitHub, Jira, Jenkins, Poetry, Terraform. Data analysis & visualization skills (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. Preferred Qualifications Record of involvement in public AI/ML discourse through conference participation or publications. Experience productionizing the use of AI/ML within a corporate setting. Additional Conditions 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. Program participants are required to purchase or lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies. Immigration Sponsorship: GM does not provide immigration‑related sponsorship for this role. Candidates who will need GM immigration sponsorship now or in the future should not apply. Relocation: This job is not eligible for relocation benefits. Any relocation costs will be the responsibility of the selected candidate. Travel: Required to travel less than 25% for this role. Remote: The role may be based anywhere in the country of work and is not expected to report to a GM worksite unless directed by the manager. Equality Statement General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. All employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state, and local laws. #J-18808-Ljbffr