Top Machine Learning Jobs in Minneapolis, MN

Develop ML and AI solutions to improve health outcomes, working with large datasets and integrating AI technology into products.

The Senior Machine Learning Engineer on the Ads Engagement Modeling team at Reddit will develop and implement advanced machine learning models to predict ad engagement rates, collaborate on new feature development, conduct systematic feature engineering, and mentor team members. This role requires a strong background in deep learning frameworks and model lifecycles.

As a Senior ML Software Engineer, you'll design cloud solutions, enhance ML pipelines, and develop infrastructure for performance and reliability in a high-scale environment.

The role involves conducting research and development in generative models for audio, collaborating on model architecture, and prototyping solutions.

This internship focuses on applying generative AI in education, including fine-tuning models, developing evaluation frameworks, and analyzing AI outputs for learning effectiveness.

Design and implement machine learning solutions on cloud platforms, engage with customers to define requirements, and oversee project delivery from inception to deployment.

The Technical Sales Engineer will leverage AI and ML to develop solutions, engage clients, conduct presentations, and oversee project implementations, ensuring alignment between client needs and Leidos' offerings.

Develop and implement machine learning algorithms, analyze datasets, and mentor team members while collaborating with product managers to refine predictions.

Develop applied ML models and end-to-end pipelines, optimize deep learning runs, clean data, and deliver insights to stakeholders.

Seeking a Machine Learning Engineer specializing in NLP to develop deep learning algorithms and enhance Entefy's communication products, requiring a strong math background and proficiency in various programming and NLP tools.

Lead the development of machine learning models for recommendations and search systems, collaborating with cross-functional teams and advocating for AI integration.

Lead and manage the ML Production Engineering team, optimizing ML Ops and Dev Ops, collaborating with engineers to develop scalable machine learning pipelines and processes.

The Lead Machine Learning Infrastructure Engineer designs and optimizes infrastructure components for scalable ML workflows, collaborates with teams, and mentors junior engineers.

Lead the development and maintenance of ML infrastructure for feature stores, impacting millions of users and mentoring team members in a collaborative environment.

The Senior Machine Learning Engineer will modernize the FinCrime ML Pipeline, automate model training, integrate data sources, and translate commercial requirements into technical solutions.

As a Software Engineer, you will design and implement tools and pipelines for AI autonomy systems, working with large datasets and collaborating with scientists and engineers.

Develop and deploy advanced machine learning models and AI tools for medication management, while collaborating with data science and healthcare teams.