(New College Graduate) Associate AI & Data Engineering Engineer
General Motors
- Location
- Warren Michigan United States of America
- Work model
- On-Site
- Level
- Entry
- H-1B history
- 267 approvals (FY2023)
- Posted
- Aug 19, 2026
Skills
About this role
Job Description
GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.) To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from. Work Arrangement: Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the office three times per week, at minimum. Location: Warren, Michigan - GM Global Technical Center – Cole Engineering Center The Team: Software-defined vehicles are revolutionizing the automotive industry, driven by technological advancements and the growing demand for intelligent, safer, and more environmentally sustainable transportation solutions. At the heart of this transformation is software—the driving force behind communication, security enhancements, real-time updates, data processing, and a seamless user experience. These innovations extend beyond consumer benefits, offering significant advantages for business owners. The adoption of advanced software solutions serves as a catalyst for increased efficiency, cost reduction, enhanced safety, improved decision-making, and higher employee satisfaction. This enables businesses to achieve their goals and stay competitive in a rapidly evolving market. Additionally, our solutions are designed to accelerate the transition to electric vehicles, contributing to the decarbonization of the transportation sector. At General Motors, we are on an ambitious journey to lead the development of next-generation software solutions for commercial fleet owners and drivers, from small and medium-sized businesses to large enterprises. As a leading OEM, our vast fleet of GM vehicles operates globally, giving us a unique advantage in controlling both in-vehicle and cloud software. This allows us to deliver seamless solutions in fleet management, energy optimization, transportation logistics, safety systems, and more.
The Role
We are seeking a new college graduate with interests across data science, AI/ML, and software engineering. In this role, you will work with data pipelines, machine learning workflows, backend services, and front-end applications. You don’t need deep expertise in every area what matters is strong foundational skills, curiosity, and the ability to learn quickly. This position offers exposure to real engineering problems, modern AI infrastructure, and end‑to‑end development workflows in a collaborative environment.
Responsibilities
Develop and maintain data pipeline, analytics workflows, and datasets that support machine learning and data-driven systems. Contribute to the design, training, evaluation, and deployment of machine learning models under the guidance of senior engineers and data scientists. Support AI infrastructure engineering, including containerized workloads, batch processing, and model-serving APIs. Write production-quality code in Python or Java or Go depending on project requirements. Build UI components or dashboards using front-end frameworks such as React or standard web technologies. Follow engineering best practices, including version control, testing, documentation, and code reviews. Collaborate with team members during sprint planning, design discussions, and technical reviews.
Minimum Qualifications
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (recent or upcoming graduate). Strong programming fundamentals. Understanding of data structures, algorithms, and basic database concepts (SQL or NoSQL). Foundational knowledge of data science or machine learning concepts, including model