Top Senior Machine Learning Jobs in Minneapolis, MN

Lead the design and delivery of AI solutions, guiding architecture decisions across data platforms and machine learning systems. Collaborate with technical teams and influence decisions while ensuring solutions meet regulatory requirements.

The Lead AI/ML Engineer will design and implement advanced AI solutions, lead engineering teams, and ensure high-quality AI systems that meet healthcare challenges. Responsibilities include collaboration with stakeholders, driving architecture decisions, and mentoring engineers.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

The AI Solutions Engagement Director is responsible for client relationship management, driving ML/AI technology adoption, and ensuring successful solution delivery in healthcare settings.

Lead and grow a team delivering provider-focused actuarial models and advisory solutions. Drive strategy for risk adjustment, capitation, and value-based contracting; integrate data science/AI into actuarial processes; oversee forecasting for Medicare ACO programs; advise executive clients using claims and revenue analytics; ensure regulatory compliance and manage budgets, timelines, and resources.

Lead the design and development of AI-powered features and platforms. Guide teams to create innovative solutions, ensure project success, and mentor team members while enhancing client relationships.

The AI Solutions Engagement Lead will cultivate client relationships, ensure effective ML/AI solutions delivery, drive value realization, and lead training initiatives in healthcare settings.

Lead design, development, deployment, and maintenance of AI/ML solutions (including LLMs and Generative AI) for healthcare. Drive adoption of responsible AI, build conversational/chatbot systems, integrate AI into cloud services, ensure production reliability, mentor engineers, and align solutions with enterprise AI strategy and product goals.

The role involves analyzing conversational data, enhancing NLP accuracy, monitoring AI model performance, and leading AI initiatives in a contact center environment.

Lead design, development, deployment, and maintenance of AI-powered solutions (LLMs, Generative AI, traditional ML) for provider-facing products. Build chatbots and conversational NLP, integrate AI into cloud (preferably AWS), ensure responsible AI practices and compliance, provide technical leadership, mentor engineers, and collaborate with product and architecture teams.

Design, implement, and maintain large-scale identity and access management solutions in public and private cloud. Implement OAuth/OIDC/SAML standards, assess and improve identity and cloud security posture, drive threat modeling and proactive security, and lead architecture initiatives for authentication, federation, SSO, and resiliency (SRE/DDoS mitigation).

Design, lead, and evolve the Channel Integrity Program to manage risks related to bribery, corruption, and fraud, utilizing predictive analytics and compliance strategies.

The AI Engagement Manager will foster relationships with top partners, facilitate adoption of AI solutions, and analyze performance using BI tools.

Lead Machine Learning Operations initiatives by developing retail-specific models and a user-friendly Model Workbench for marketers. Ensure product development aligns with customer needs.

Lead the product vision, strategy, and execution for Consumer Risk within Checkout at Affirm, focusing on credit decisioning, pricing, and fraud prevention while managing a team of Product Managers and collaborating with various functional teams.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

As Principal Product Manager for the Agentic Platform, you will set the vision and strategy for AI infrastructure, drive product development, and facilitate adoption across teams.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

The Senior Engineering Manager will lead multiple growth engineering teams to build products, improve engineering quality, and drive significant business impact, focusing on user growth through innovative strategies while ensuring high-quality execution under deadlines.

Lead deep-dive analyses into account takeover and fraud, design and implement real-time defenses, collaborate with product/engineering/data science, run incident response, and deliver actionable insights to protect users while preserving UX and core metrics.

Lead teams in developing computer vision and machine learning solutions for AI dash cameras, focusing on safety insights and risk monitoring. Oversee model lifecycle and collaborate with cross-functional teams for feature deployment at scale.

Lead the design and implementation of ML training systems, manage a team, promote engineering culture, and drive product development.

The Engineering Manager will lead a team in developing a Dispatch Optimization platform, focusing on data science, ML engineering, and operational efficiency, while fostering talent and ensuring project delivery.

Join as a Senior AI/ML Engineer to develop cloud-based AI solutions involving NLP and OCR, mentoring team members, and delivering impactful AI-driven automation.

The Technical Talent Partner will manage the recruiting process for critical roles in Technology and Product, leveraging data-driven methodologies, ensuring talent quality, and navigating offer negotiations.