Top Machine Learning Jobs in Minneapolis, MN

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

The Senior Full Stack Engineer will develop AI/ML features in ClickHouse Cloud, integrating databases with AI capabilities, ensuring robust API design, and building user-friendly interfaces.

This role involves designing, developing, and scaling machine learning systems for payment flows and recommendations, leading technical initiatives, and optimizing complex financial decision systems.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

The Senior Machine Learning Engineer will develop ML infrastructure, deploy ML models, monitor performance, and mentor junior engineers. Collaboration with cross-functional teams is essential.

The Staff Machine Learning Engineer will design, develop, and deploy scalable ML algorithms, lead experimentation, and collaborate across teams to enhance AI solutions.

The Machine Learning Engineer will design, build, and operate data systems, optimizing data flows and integrating AI/ML models, mainly on AWS.

Lead the design and implementation of machine learning platforms at Yahoo, focusing on architecture, governance, and system performance while mentoring teams and influencing industry trends.

The Applied Scientist Intern will develop and deploy AI models, build ETL pipelines, and collaborate to enhance AI quality in legal tech.

Design and optimize AI infrastructure, ensuring reliability and efficiency. Lead projects, create ETL pipelines, and support ML workload operations.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

Drive technical strategy for ML applications, enable advanced model architectures, improve system efficiency, and mentor junior engineers.

Develop and implement machine learning models, analyze data, collaborate on solutions, and optimize systems for scalability while staying updated with AI advancements.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

The Staff Software Engineer will design, build, and scale ML systems to enhance user engagement through recommender systems and collaboration with cross-functional teams.

As a Senior ML Platform Engineer, you will develop AI-driven solutions, enhance model performance, and collaborate across teams to optimize data processes.

Lead the design and deployment of machine learning models for personalized healthcare, mentor engineers, and collaborate across teams to improve ML infrastructure.

Lead the architecture and development of machine learning systems for personalized care, treatment intelligence, and automation at scale. Collaborate with cross-functional teams and mentor engineers.

As a Sr. Machine Learning Engineer, you will develop and deploy ML models, enhance care personalization, and mentor teams while optimizing workflows.

The Principal Machine Learning Engineer will architect and scale ML systems for personalized healthcare. Responsibilities include system design, optimization, technical leadership, and mentoring within the team.