Top Machine Learning Jobs in Ogden, UT

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

Develop and maintain web-based tools for AI/ML practitioners, improve model observability, enhance user experience, and collaborate cross-functionally. Drive product excellence and improve systems and codebase.

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

As a Senior Machine Learning Engineer, you'll develop and optimize ML systems, implement pipelines, and collaborate with cross-functional teams to enhance Yahoo's data capabilities.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

The Principal Machine Learning Engineer will lead the design and implementation of ML models and data architectures for HelloData, ensuring production readiness and system scalability while collaborating with product teams.

As a Staff Software Engineer, you will lead the development of Cake's AI platform infrastructure, focusing on building, operating, and improving ML systems. The role requires collaboration with customers to address ML challenges and enhance platform capabilities, emphasizing ownership and operational excellence.

Seeking a Founding ML Engineer to design and deploy LTV prediction systems, handle MLOps, and collaborate with product teams. Requires strong ML experience and knowledge of cloud environments and data stacks.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

As a Senior Staff Machine Learning Engineer, drive AI safety initiatives, design monitoring systems, and collaborate cross-functionally to ensure robust, safe AI usage in community support products.

Lead the Generative AI engineering team in building and executing AI strategies, managing platform lifecycle, and collaborating with stakeholders for impactful AI solutions.

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

The Staff ML Ops Engineer builds and maintains infrastructure for ML applications, ensuring they are robust and production-ready, while collaborating with data scientists and ML engineers.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

The Principal Machine Learning Engineer will lead ML lifecycle projects, developing AI strategies, and implementing advanced machine learning solutions for government clients, while ensuring data integrity and operational efficiency.

The Senior Software Engineer will design and build infrastructure for ML model training and deployment, focusing on AWS technologies, reliability, and collaboration with ML teams.

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

The Senior Machine Learning Engineer at SmarterDx will deploy, maintain, and optimize machine learning models, collaborating across disciplines to integrate these solutions and improve clinical AI outcomes.