AI Platform Engineer

AI Platform Engineer at General Motors

As an AI Platform Engineer on the Enterprise AI team at General Motors, you will play a critical role in shaping GM’s future through high-impact AI systems. You will implement advanced AI technologies and integrate them into GM’s business strategies, culture, and operational workflows. This is a hands-on technical contributor role focused on building core infrastructure components for AI/ML workflows, working closely with other engineers and teams to deliver performant, production-grade systems.

What You’ll Do:

• Develop and test cutting-edge AI infrastructure, optimizing machine learning and AI-driven applications across GM’s global platforms.
• Collaborate with cross-functional teams (data scientists, software engineers, product teams) to bring AI solutions into production at scale.
• Implement robust, high-performance software systems with a focus on scalability, security, and efficiency.
• Lead technical initiatives in validation, deployment, and monitoring in real-world environments.
• Implement integrations with diverse data sources and SaaS platforms using APIs, while orchestrating workflows through internal and third-party tools.

Your Skills & Abilities (Required Qualifications):

• 7-10 years’ experience required of software engineering, fluency in .NET, Python or Java.
• Bachelor’s degree in Computer Science, Data Science, AI/ML, or equivalent experience.
• Understanding of machine learning, deep learning, and statistical modelling.
• Familiarity with cloud-based AI/ML platforms (AWS, GCP, Azure) and containerisation using Docker and Kubernetes.
• Experience adapting AI integrations with tools such as Slack, Google Workspace, Moveworks, Glean, Copilot, Workday and/or ServiceNow.

What Will Give You A Competitive Edge (Preferred Qualifications):

• Self-motivated, strong execution, impact-delivering oriented.
• Knowledge of algorithms, distributed systems, and API development.
• Excellent problem-solving skills, with the ability to learn and deliver in a fast-paced environment.
• Experience with natural language AI, such as customization, summarization and translation.

Key Skills/Competency:

• AI Infrastructure Development
• Machine Learning Optimization
• Cloud Platforms (AWS, GCP, Azure)
• Containerization (Docker, Kubernetes)
• Software Engineering (.NET, Python, Java)
• API Integration
• Distributed Systems
• Deployment and Monitoring
• Statistical Modeling
• Natural Language AI