Top Machine Learning Jobs in Minneapolis, MN

Lead the AI/ML Engineering team to transform healthcare claims processing, driving automation and operational intelligence across claims systems.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

Lead enterprise AI and analytics architecture: design AI-ready data platforms, implement data cataloging, semantic layers, feature and vector stores, ensure governance/privacy-by-design, enable data products for BI, ML, and AI agents, and advise executive leadership while mentoring architects and engineers.

Develop and deploy AI/ML models in the pharmacy domain, focusing on Generative AI technologies and collaborating with operations and capability teams.

The AI/ML Engineer will develop and deploy AI solutions using Generative AI technologies, focusing on LLMs and frameworks like LangGraph and LangChain. Responsibilities include building APIs, deploying ML models on cloud platforms, optimizing solutions, and collaborating with stakeholders.

Lead enterprise IT strategy and execution, align technology roadmap with business goals, modernize operations (ERP, shop-floor automation, supply chain), oversee architecture, cybersecurity, disaster recovery, and analytics; manage IT budget, governance, and high-performance teams to drive digital transformation and operational efficiencies.

The Director leads AI and emerging technology risk consulting, advising on governance, ethical use, and developing risk frameworks, while managing client engagements and sales strategies.

Lead a full-stack engineering team building, deploying, and operating production-grade AI/ML applications (LLMs, deep learning, agentic systems). Drive technical architecture, infrastructure, data, APIs, reliability, security, and ML Ops. Coach and develop engineers, align stakeholders, manage roadmaps, and ensure scalable, maintainable solutions that deliver measurable business value.

Lead and scale AI/ML engineering teams, architect ML platforms, build MLOps pipelines, and ensure the governance of ML systems.

The Principal Cloud Architect defines AI/ML architecture, ensures standards, mentors teams, and aligns mobile-first strategies across multiple platforms.

Support development of pricing arrangements, financial models, budgets and AFAs for a law firm. Produce pricing analyses, competitive market research, and performance metrics. Collaborate with attorneys, IT, and data teams to implement pricing tools (Elite 3E, Iridium), leverage AI/analytics for forecasting, and train stakeholders on pricing technology.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

Lead product initiatives from discovery through launch for healthcare SaaS products using analytics and ML. Own roadmap, prioritize backlog, partner with engineering/design/data, use qualitative and quantitative evidence, and drive adoption and measurable customer impact.

Build and operate ML training and serving infrastructure by designing, developing, and launching backend systems. Collaborate across teams to decompose projects, support operations and on-call, create monitoring and metrics, perform code reviews, and contribute to developer velocity and platform reliability.

Own Cash Application and Deduction Resolution Management products end-to-end. Lead discovery, define requirements, prioritize roadmap, partner with engineering/design/sales, ensure financial accuracy, build ERP integrations, drive launches, and maintain product quality and customer-focused outcomes.

Lead implementation of enterprise AI platforms, governance, and high-impact analytics use cases. Drive end-to-end delivery from experimentation to production, mentor teams, embed responsible AI practices, and partner with cross-functional stakeholders to operationalize AI across the business.

The Enterprise Architect leads architectural strategy and integration for technology and processes while aligning IT investments with business goals. Responsibilities include overseeing cloud modernization, governance, and communication with stakeholders.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Lead the development of agentic AI systems for real estate, focusing on long-horizon, supervised experiences. Architect collaborative systems and define success metrics while mentoring a small team.