Top Machine Learning Jobs in Salt Lake City, UT

As Director of Fraud Model Development, you'll lead a team to innovate fraud risk strategies using AI/ML, oversee model development, and ensure performance optimization.

Analyze complex challenges and enhance AI infrastructure through advanced machine learning, while mentoring engineers and developing production-grade systems.

As a Senior Machine Learning Engineer, you will design and implement advanced machine learning models and solutions, collaborate with stakeholders, mentor junior engineers, and enhance product capabilities using AI technologies.

As a Staff Machine Learning Engineer, you'll define technical strategies, design ML models, implement real-time ML pipelines, and deploy systems at scale to enhance Coinbase's operations and user protection.

Develop and deploy machine learning models for fleet management solutions. Collaborate with teams on data processing, model training, and real-time deployment.

Lead machine learning initiatives at Vetcove, designing, building, and deploying ML models to improve decision-making in veterinary practices. Collaborate with teams to integrate models and establish best practices, while mentoring peers and enhancing real-world outcomes.

As a Senior Applied Scientist, you will leverage multimodal data to develop ML models, collaborating across teams and optimizing performance based on real-world feedback.

As a Machine Learning Engineering Intern, you will support the development and deployment of machine learning models, assist in integrating tools, participate in code reviews, and work in an Agile environment.

The Senior Machine Learning Engineer will design and implement machine learning architecture, develop models, and collaborate with teams to build data-driven features for a CRM product.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

The Distinguished Machine Learning Engineer will drive modern technology adoption, solve complex business problems, mentor talent, and lead data engineering initiatives.

Design and build scalable AI/ML products, collaborate with cross-functional teams to implement AI solutions, and enhance data strategies for marketing.