Top Machine Learning Jobs in Minneapolis, MN

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Own and prioritize a portfolio of AI opportunities aligned with business strategy and measurable value. Define problems, develop business cases and cost-benefit analyses, establish success metrics, and prepare initiatives for governance and funding decisions. Influence executives and cross-functional stakeholders across business, technology, data, and external partner teams. Support transitions from validated opportunities into scalable solutions and partner with delivery teams through execution.

A 10-week technology internship where students collaborate on impactful projects, receive mentoring, present work to leaders, and explore how software, AI, and technology can improve healthcare systems. Interns work full-time in person in Eden Prairie, Minnesota, gaining hands-on experience and professional development while contributing to a cohort-based technology program.

Leads end-to-end implementation, governance, review, adoption, and monitoring of AI use cases across the People Technology function. Partners with HR, engineering, data science, legal, privacy, security, and compliance stakeholders to assess risks, establish success measures, build implementation frameworks, track value realization, and ensure responsible AI standards and operational readiness. Provides executive reporting and advises HR leaders on compliant, measurable AI adoption.

Leads enterprise AI and machine learning platform adoption, go-to-market strategy, releases, onboarding, training, documentation, and support. Partners with product, engineering, business, governance, security, and risk teams to manage dependencies, improve workflows, prioritize roadmaps, and ensure responsible AI readiness. Advises senior leadership, evaluates technical and data readiness, develops AI opportunity pipelines, and communicates adoption, business impact, quality metrics, and risk posture through executive-level roadmaps and dashboards.

Manage and prioritize an AI opportunity portfolio, translating ambiguous demand into decision-ready initiatives. Develop business cases, cost-benefit analyses, product narratives, success metrics, and governance recommendations. Align business, technology, data, and external stakeholders; influence executive funding and sequencing decisions; and support the transition of validated opportunities into scalable AI solutions.

Lead the modernization of Chewy’s fulfillment technology and warehouse management systems. Define architecture, write production code, build resilient cloud and edge systems, develop mobile warehouse applications, establish workflow and integration patterns, and integrate analytics, AI, robotics, and decisioning systems. Provide technical direction across teams, lead design and code reviews, improve engineering practices, and mentor engineers while ensuring high availability, observability, auditability, and operational continuity.

Lead AI/ML data science projects for payment integrity, from stakeholder requirements through production deployment. Develop, evaluate, monitor, and refine machine learning models that detect payment issues and prioritize clinical audit inventories. Collaborate with engineering, infrastructure, operations, and business teams; communicate methodologies and insights to technical and non-technical audiences; and ensure compliance with ethical, legal, regulatory, and organizational standards.

Leads enterprise AI transformation across Medicare shopping, sales, agent, partner, and support experiences. Owns the unified product portfolio strategy, roadmap, AI voice and conversational IVR experiences, cross-channel journey continuity, shared knowledge and orchestration capabilities, responsible AI governance, measurement, and operational readiness. Partners with engineering, architecture, data, design, compliance, and operations teams to deliver scalable AI-enabled products, improve customer and employee experiences, and develop a multidisciplinary product organization.

Leads the strategy, architecture, development, deployment, monitoring, and improvement of applied AI, NLP, LLM, voice analytics, and automation solutions. Translates ambiguous business needs into scalable analytical architectures and production systems, establishes evaluation and governance standards, oversees data pipelines and model operations, troubleshoots complex issues, presents recommendations to stakeholders, shapes technical roadmaps, and mentors data scientists.

Monitors AI solution registrations, security reviews, compliance evidence, approved use records, telemetry, and control performance. The role triages alerts, policy violations, exceptions, incidents, and control gaps; supports root cause analysis and remediation; maintains audit-ready workpapers, logs, repositories, and metrics; and coordinates with engineering, application, identity, data protection, vendor risk, and Responsible AI teams. It also provides operational support for AI security governance processes.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Supports production data science capabilities by monitoring models, automations, pipelines, dashboards, and decision-support tools. Troubleshoots issues, evaluates performance, maintains documentation, and recommends improvements. Develops scalable data pipelines, workflows, analytical processes, dashboards, and AI-enabled solutions while conducting ad hoc analyses and supporting validation and deployment. Partners with senior data scientists and business stakeholders to operationalize research, communicate findings, and expand ownership across analytical portfolios.

Leads AI/ML engineering teams and technical strategy for enterprise-scale healthcare and pharmacy solutions. Oversees development, deployment, governance, MLOps, security, and operations for generative AI, LLM, NLP, predictive analytics, and agentic AI capabilities. Partners with product, engineering, data science, and executives to align technology with business goals, evaluate emerging technologies, improve automation, and develop engineering talent.

Leads the AI/ML engineering roadmap and provides technical direction across machine learning, generative AI, agentic AI, NLP, and predictive analytics. Designs, trains, evaluates, and deploys production models; builds LLM, RAG, and AI-agent applications; establishes MLOps pipelines, monitoring, governance, responsible AI, and cloud infrastructure. Mentors engineers and data scientists, partners with business leaders, and communicates solutions and outcomes to executives.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Design, build, deploy, and support scalable Java microservices on AWS. Provide technical leadership, architectural direction, code reviews, troubleshooting, proof-of-concept development, and cross-functional collaboration. Work with high-throughput data, messaging systems, distributed architectures, observability, and AI-assisted development tools. Participate in on-call support, mentor engineers, lead architectural initiatives, and deliver reliable SaaS platform features.

The Senior Data Scientist supports Customer Success through deep-dive analysis, predictive modeling, causal inference, experimentation, and KPI development. The role analyzes churn, retention, renewals, upsell opportunities, and revenue trends; diagnoses metric shifts; builds data pipelines and dashboards; and develops AI/LLM-powered solutions. The scientist collaborates with stakeholders, communicates insights, improves data quality, and measures the impact of customer success initiatives and product changes.

Own the strategic vision and roadmap for Coursera’s search experience, including conversational, personalized, semantic, multilingual, and AI-driven discovery. Partner with engineering, design, research, data science, marketing, and product teams to improve search accuracy, conversion, and learner engagement. Lead experimentation, KPI measurement, competitive analysis, and revenue-focused personalization initiatives across a global learning platform.

Lead technical client onboarding, migrations, solution design, integrations, data orchestration, troubleshooting, and project delivery for Movable Ink’s AI-powered personalization platform. Partner with clients and internal teams to implement custom workflows, APIs, webhooks, and data solutions. Conduct training and workshops, provide product expertise, advise on roadmap improvements, and support long-term client success across email and mobile marketing programs.

Leads underwriting innovation by identifying opportunities for AI, automation, and emerging technologies to improve workflows, decisions, and user experiences. Partners with underwriting, product, and technology teams to translate business challenges into concepts, evaluate solutions and feasibility, and support implementation. Requires underwriting expertise, analytical and communication skills, stakeholder alignment, and experience applying technology to workflow or process improvements. The role is remote within the U.S. with up to 10% travel.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Develop and productionize GenAI, LLM, machine learning, and analytics solutions for ASIC semiconductor engineering. Build agentic systems, RAG workflows, predictive models, and failure-analysis tools; deploy and monitor AI solutions in cloud and enterprise environments; collaborate with architecture, design, data science, and IT teams; and communicate technical findings while identifying opportunities to improve engineering productivity, quality, cost, and cycle time.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Leads high-visibility product programs focused on market adoption, analyst relations, customer advisory boards, executive briefings, and industry events. Translates technical product roadmaps into compelling market value propositions, synthesizes analyst and customer feedback, and provides actionable insights to product leadership. Partners cross-functionally with Product, Marketing, and executive stakeholders while supporting strategic initiatives and external-facing communications.