Intern - Technology Innovation Lab

Why GM Financial? 
GM Financial is the wholly owned captive finance subsidiary of General Motors and is headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, with operations in North America, South America, and the Asia Pacific region. Through our long-standing relationships with auto dealers, we offer attractive retail financing and lease programs to meet the needs of each customer. We also offer commercial lending products to dealers to help them finance and grow their businesses.

At GM Financial, our team members define and shape our culture — an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.

Our Purpose: We pioneer the innovations that move and connect people to what matters.

This position will be posted until filled. 

About this role:

Our Tech Innovation Lab is seeking interns with a passion for technology innovations in the financial sector. Ideal candidates should be pursuing a degree in Computer Science, Engineering, or a related field, with an interest in technologies like AI, Machine Learning, Big Data Analytics, and Server less computing. While technical skills are important, we also value creative thinking and the ability to approach problems from different angles. Basic programming skills in languages such as Python, JavaScript, .NET or Java are expected. The intern will be involved in research and development projects focusing on the application of these technologies in the financial industry, assisting in the development and prototyping of new solutions, and contributing to the lab’s initiatives in implementing advanced tech solutions to address financial challenges. A keen interest in financial technologies and a willingness to engage with emerging tech trends are crucial for this role.

In this role you will:

• Assist in evaluating, researching, experimenting with computational learning technologies in a lab to keep pace with industry innovation while assessing business impact and viability for use cases associated with efforts in hand.
• Collaborate with statisticians, data engineers, application developers, and related groups to inform on and highlight capabilities of emerging technologies and to enable the adoption of these modern technologies, computational learning, and associated algorithms.
• Work closely with statisticians, data engineers, application developers, other IT counterparts, and business partners to develop, integrate and deploy computational learning as part of applications.