Top Machine Learning Jobs in Minneapolis, MN

The role involves building end-to-end modeling pipelines, developing models, delivering insights to stakeholders, and collaborating with a technical team in a fast-paced environment.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

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.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

The Senior Engineering Manager at Planet leads the engineering team, focusing on delivering products for Defense Intelligence. Responsibilities include mentoring engineers, refining processes, and collaborating across teams for effective deployment of technology.

Lead technical engagement across pre-sales, deployment, and post-sales for on-premises quantum systems. Drive customer success, inform product development, support sales with deep HPC/AI/optimization expertise, present at industry events, and translate customer needs into deployment strategies and R&D feedback.

The AI Engineer will design, implement, and prototype GenAI and ML solutions to enhance operational intelligence and efficiency in investment services.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

As a Research Intern, you will prototype and productionize research in AI and cryptographic schemes, collaborating with teams for real-world impact.

The VP of Marketing will scale marketing functions, drive demand generation, build teams, establish marketing strategies, and coordinate with sales to enhance pipeline and revenue growth.

Lead the Mid-Market Sales team to connect technical organizations with AI and data science tools, driving adoption and growth through value-based selling and strong partnerships with engineering teams.

As a Product Manager for Risk, you'll design fraud prevention tools, manage cross-functional teams, and improve fraud detection methods.

The Senior Backend Data Engineer will extend data ingestion and processing pipelines, build APIs and backend services, and provide technical leadership.

The Director of Data Engineering, ML & AI leads data strategy and AI capabilities, managing a team to enhance data infrastructure, machine learning systems, and sustainability analytics while driving company-wide AI initiatives.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

The Senior Machine Learning Engineer will build and enhance models and systems for classifying and enriching Internet data, collaborating with various teams to improve data quality and insights.

Lead the development and deployment of ML models to optimize pricing and enhance customer experiences. Drive AI strategies, conduct research, and collaborate across teams.

The Enterprise Account Executive drives growth through AI and ML SaaS solutions in the food and beverage industry, managing complex sales cycles and building relationships with key stakeholders.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Machine Learning Engineer will design and implement AI/ML projects on AWS, optimize data architectures, and ensure secure data management.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

The role involves deploying, optimizing, and maintaining ML-driven motion planning and control algorithms for autonomous driving, collaborating across teams to ensure reliability under performance and safety constraints.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.