Job Description
Work arrangement: This role is remote; however, 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 at least three times per week.
The AV Safety Engineering Analytics team is on the lookout for an AI/ML Engineer with expertise in vehicle engineering, AI/ML, and cloud processing.
This team is crucial in supporting various teams throughout the company by leveraging a wide array of data and analytical capabilities for AV safety-related decision-making. We focus on efficiently integrating continuously flowing data from vehicle systems, company databases, third-party services, federal agencies, and state DOTs to enhance system design and evaluate driving performance. The focus is on proactive continuous uptime analyses and providing support for specific investigations.
If you have a passion for the advancement of autonomous vehicle technology and safety, and enjoy transforming complex data into actionable insights, this position presents a fantastic opportunity to contribute to the future of transportation safety in an engaging and innovative environment.
As a member of the AV Safety Engineering Analytics team, you will be the go-to expert for implementing effective AI/ML methodologies for safety assurance analytics. Collaborate closely with cross-functional teams and stakeholders to identify opportunities for the use of AI/ML in organizing safety-related data and assessing driving performance. Work with your team to address challenges and devise solutions leveraging your AI/ML knowledge.
What You'll Do
- Contribute to building a robust data analytics infrastructure that meets the safety assurance needs of various stakeholders during the automated vehicle development and deployment phases, incorporating both real-world and simulated data.
- Utilize your AI/ML knowledge to develop reliable and explainable methods to validate the safety performance of AI/ML-based automated driving systems.
- Mentor team members in the effective use of AI/ML to advance the goals of the SAFE-ADS department and the AV Safety Engineering Analytics team.
- Establish metrics for monitoring development operations and deployment, and set criteria for launch readiness.
- Create methods to utilize diverse internal and external data sources for AI/ML-based safety monitoring to support ongoing safety assurance activities.
- Implement cloud-based, continuous uptime analytics solutions for monitoring driving performance, including generating interactive visualizations and periodic reports.
- Contribute to decisions on the application of AI/ML approaches within automated driving systems, providing technical expertise to guide leadership on maintaining their trustworthiness and explainability.
- Use your AI/ML skills to shape GM's data sourcing and processing strategy for AV safety assurance, engage in discussions influencing evolving standards, and lead thought leadership initiatives that bolster GM's standing in the autonomous vehicle market.
- Represent SAFE-ADS in AI/ML discussions across Global Product Safety, Systems, and Certification activities.
- Identify and drive opportunities to enhance the efficiency, quality, and transparency of safety analytics within GPSSC and throughout GM.
Your Skills & Abilities (Required Qualifications)
- Master's degree in Computer Science, Mechanical Engineering, Vehicle Engineering, Physics, or related field; or equivalent practical experience focused on AI/ML.
- 10+ years of experience with large scale analyses of vehicle-related data.
- 5+ years of experience in safety-critical AI/ML systems in automotive applications.
- Machine Learning & AI: Extensive experience in building large-scale models with a strong emphasis on E2E validation. Familiarity with Large Language Models (LLMs), Generative AI, RAG, Deep Learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering.
- AI Standards and Evolving Regulations: Knowledge of ISO/PAS 8800, NIST AI Risk Management Framework, EU AI Act (2024-2027), and other industry standards pertaining to autonomous vehicles, aerospace, or robotics.
- Programming & Frameworks: Proficient in Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL.
- Cloud & Big Data: Experience with cloud-based large-scale processes, including notifications, queuing, containerization, and optimization. Proficient in Microsoft Azure, AWS, or Google Cloud Platform.
- Deployment & MLOps: Knowledge of CI/CD, MLflow, Model Monitoring & Versioning, Docker & Kubernetes, GitHub, Jira, Jenkins, Poetry, Terraform.
- Data Analysis & Visualization: Familiar with Tableau, PowerBI, Plotly/Dash, Shiny, Pandas, NumPy.
- A proven record of technical leadership in AI/ML applied to safety-critical systems.
- Strong communication and collaboration skills, with the ability to thrive in team settings.
- A proactive attitu