Find Jobs

Find Jobs Near You – Available Work in Your Location

Skip to job details

Back to Results

Apply for this opportunity

To apply for this job, you'll continue to an external website or email application.

Apply Offsite

United Wholesale Mortgage LLC

AI Engineer III

Pay: Not specified

Posted: 4 weeks ago

Location: Pontiac, MI (Onsite)

Last Updated: 3 days ago

Hours: Full-Time

Expires: 10/11/2026

Career Insights for Generative Artificial Intelligence Engineer

See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.

Scorecard

Based on Michigan data

Review key factors to help you decide if this role fits your goals. How is this calculated?

Were these scores useful?

What they do

A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.

$123,000 / year median in Michigan

Explore Career

Job Description

United Wholesale Mortgage is hiring an AI Engineer III for a 100% on-site position in Pontiac, MI.

Duties:

Conduct research on cutting-edge techniques in the field of generative

AI:

Stay updated with the latest research and advancements in the field of generative AI. This includes reading academic papers, attending conferences, and experimenting with new techniques and algorithms. Collaborate with cross-functional teams to integrate these models into larger systems: Work closely with other teams within the organization such as software engineers, data scientists, product managers etc., to ensure that your models can be effectively integrated into our products and services. Evaluate the performance of generative models and make necessary adjustments for optimal results: Regularly test your models against benchmarks and real-world scenarios to evaluate their performance. Make necessary tweaks and adjustments to improve their accuracy and efficiency. Stay up-to-date with the latest advancements in AI and machine learning, specifically in the area of generative models: Continuously learn about new developments in your field so you can apply the latest techniques to your work. Document and present your findings to both technical and non-technical stakeholders: Clearly communicate your methodologies, findings, and insights to different stakeholders within the organization. This could include writing technical reports for other engineers or presenting high level summaries to executives.