Design, 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.
Design and 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.
Design and implement integrations with diverse data sources and SaaS platforms using APIs, while orchestrating workflows through internal and third-party tools.
Optimize cloud resources for cost, performance, and scalability.
Mentor and guide junior engineers, fostering a culture of innovation and technical excellence.
Requirements
10+ years’ experience required of software engineering, with a strong background in Python, Java and .NET.
5+ years’ experience managing an engineering team
Bachelor’s degree or higher in Computer Science, Data Science, AI/ML, or equivalent experience.
Ability to define and propose innovative solutions to business problems and projects that may begin with ambiguous requirements and requests.
Expert knowledge of cloud platforms such as AWS, Azure, or GCP, and container orchestration technologies.
Experience adapting and designing AI integrations with tools such as Slack, Google Workspace, Moveworks, Glean, Copilot, Workday and/or ServiceNow.
Experience with DevOps practices and CI/CD tools, pipelines, and scripting for automation.
Benefits
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonJava.NETAI infrastructuremachine learningsoftware systems designcloud optimizationDevOps practicesCI/CDscripting