Top Machine Learning Jobs in Minneapolis, MN

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Manage a portfolio of customers as primary contact, drive adoption and retention, respond to support requests, troubleshoot issues with product teams, identify upsell and renewal opportunities, and provide customer insights to product and engineering.

Interns will prototype rapidly, iterate, and contribute to open-source projects at the intersection of AI and cryptography.

The Senior Vice President of Underwriting will oversee underwriting outcomes across multiple lines, driving growth and improving loss ratios through data-driven strategies and leadership.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

The Machine Learning Engineer will build data-intensive products, deploy ML models, analyze datasets, and collaborate with product teams to enhance Nextdoor's platform.

Lead early-stage product experimentation and prototype spatial, 3D, and AI-driven experiences. Translate ML/CV capabilities into testable products, partner with engineering on execution, shape strategy across the portfolio, and communicate outcomes to stakeholders.

Join Invoca's Talent Community to stay updated on job openings and to explore exciting career opportunities across various departments.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

The Sr AI Platform Specialist Solution Architect will provide technical sales support for AI solutions, architect AI systems, and facilitate customer engagement, focusing on removing blockers for adopting Red Hat AI.

The Data Scientist L6 leads the technical strategy for Netflix's Games Portfolio Team, focusing on forecasting, metrics ecosystems, audience insights, and model development while mentoring team members and ensuring production-grade data products.

Lead development and execution of data-driven audit strategies for insurance and PBM clients. Analyze large datasets, design analytics solutions, create dashboards, perform statistical profiling and sampling, ensure regulatory compliance, manage project budgets and client communications, and coach junior staff to improve examination efficiency and effectiveness.

As a Scientist II, you will design and implement studies for natural language applications, manage cross-program analysis, and ensure coherence in automated scoring systems.

The Staff Technical Program Manager will manage robotics projects, oversee cross-functional teams, ensure timely delivery, and maintain effective communication across stakeholders.

The Simulation Engineer will work on AI solutions for CAE workflows, integrate AI technologies, engage with customers, and enhance AI software products.

As a Senior Engineer, you will design and scale ML models for fraud detection, develop MLOps pipelines, and collaborate with cross-functional teams.

As a P&C Actuary, you will assess insurance risks, review regulatory compliance, support audit teams, and document findings while nurturing client relationships and contributing to practice development efforts.

As a Senior Machine Learning Platform Engineer, you'll architect a scalable ML platform, collaborating with teams to ensure compliance, optimize performance, and guide best practices in ML workflows.

Build and own ML platform infrastructure and tooling to enable model development, deployment, monitoring, and iteration. Lead realtime model monitoring, experiment tracking, reproducibility, and operational reliability to scale fraud-prevention ML systems in production.

Manage AI/ML projects from Proof of Concept to Minimum Viable Product using Agile methodologies while ensuring stakeholder communication and project alignment.

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

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Lead QA for AI/ML features: design and execute test plans, build Python automation to validate LLM outputs, guardrails, and data pipelines; perform regression, security/privacy validation, and analyze logs/metrics to ensure reliability.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.