Tech Stack
AWSAzureCloudDockerGoogle Cloud PlatformJavaKubernetes.NETPythonServiceNow
About the role
- 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.
Requirements
- 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, Move works, Glean, Copilot, Workday and/or ServiceNow.
- 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
.NETPythonJavamachine learningdeep learningstatistical modellingcloud-based AI/MLDockerKubernetesAPI integration
Soft skills
collaborationleadershipcommunicationproblem-solvingorganizational skills