[Skip To Content]

(New College Graduate) Associate AI & Data Engineering Engineer

  • Localização
    • Austin, Texas
    • Mountain View, California
    • Warren, Michigan
  • Tipo de trabalho Full time, Entry Level
  • Postou
  • Job Requisition JR-202601970

Descrição

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 training and evaluation.

  • Familiarity with at least one modern front-end framework or a willingness to learn.

  • Ability to work with Linux-based environments and developer tools (Git, CLI, build systems).

  • Interest in modern cloud, AI, and platform technologies.

What will give you a Competitive Edge (Preferred Qualifications):

  • Internship, research project, or academic experience involving ML, data engineering, cloud platforms, or software development.
  • Exposure to Docker, Kubernetes, containerized development, or workflow orchestration systems.

  • Experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow.

  • Experience building web interfaces, dashboards, or interactive visualizations.

  • Familiarity with cloud providers (AWS, Azure, or GCP) and basic compute/storage concepts.

What Success Looks Like in the First 3–6 Months

  • Contributing meaningful code to production or pre‑production environments.

  • Taking ownership of tasks related to AI infrastructure, data pipelines, ML workflows, or application components.

  • Developing a working understanding of the team’s architecture, tooling, and deployment processes.

  • Demonstrating initiative in learning new technologies and participating actively in team discussions.

  • Building confidence in debugging, documenting, and collaborating across the engineering lifecycle.

Why This Role Is a Strong Fit for New Graduates

  • Broad exposure across AI, data engineering, and full-stack development, allowing you to explore multiple career paths.

  • Mentorship from experienced engineers and opportunities for technical growth.

  • Ability to work on impactful systems and contribute to production-level AI capabilities.

  • A collaborative environment that values learning, experimentation, and continuous improvement.

What you’ll get from us (Benefits):

  • GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

  • This job may be eligible for relocation benefits.

Informações sobre diversidade

A General Motors está comprometida em ser um local de trabalho que não só é livre de discriminação ilegal, como estimula verdadeiramente a inclusão e integração. Acreditamos enfaticamente que a diversidade na força de trabalho cria um ambiente no qual nossos colaboradores podem crescer e desenvolver melhores produtos para nossos clientes. Incentivamos os candidatos interessados a analisar as principais responsabilidades e qualificações de cada função e a se candidatar a qualquer cargo que corresponda a suas habilidades e capacidades. Os candidatos no processo de recrutamento podem, quando aplicável, ser solicitados a concluir com sucesso uma ou mais avaliações relacionadas à função e/ou uma seleção pré-emprego antes de iniciar o emprego.  Para saber mais, acesse Como contratamos.

Declaração de Igualdade de Oportunidades de Emprego (EUA)

A General Motors tem orgulho de ser um empregador que oferece oportunidades iguais.  Todos os candidatos qualificados serão considerados para o emprego, independentemente de raça, cor, religião, sexo, orientação sexual, identidade de gênero, origem nacional, deficiência ou status como veterano protegido. 

Adaptações (EUA e Canadá)

A General Motors oferece oportunidades a todos os candidatos a emprego, incluindo pessoas com deficiências. Se você precisa de uma adaptação razoável para ajudá-lo na sua pesquisa de cargos ou solicitação de emprego, fale conosco pelo e-mail [email protected] ou pelo telefone 800-865-7580. No seu e-mail, inclua uma descrição da adaptação específica que você está solicitando assim como o nome do cargo e o número de requisição do cargo ao qual está se candidatando.