Top Machine Learning Jobs in Minneapolis, MN

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Research intern supporting advanced analytics and new product development for revenue management. Responsibilities include preparing and analyzing data, identifying problems, designing and implementing solutions, researching forecasting, pricing, optimization, generative AI, and machine learning applications, presenting findings, and producing technical documentation. The role involves Python, SQL, Pandas, LLMs, RAG, and prototyping with tools such as LangChain and visualization frameworks.

Leads People Analytics enablement and BI strategy, overseeing semantic models, certified data products, metric governance, data foundations, advanced analytics enablement, demand prioritization, and adoption. Partners with People Analytics, IT, and HR Strategy teams to create trusted workforce data, reusable semantic assets, and decision-ready insights. Manages teams and operating models while driving data quality, governance, certification, self-service analytics, AI access, and scalable insight delivery across the enterprise.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Develop and enhance data analytics solutions for Internal Audit, including automated testing, continuous monitoring, dashboards, reporting, risk analysis, and anomaly detection. Partner with audit teams, data owners, and stakeholders to analyze complex data, document procedures and findings, improve audit processes, and evaluate responsible applications of AI, machine learning, and automation.

Own and scale Jellyfish’s security engineering program, including strategy, architecture, secure SDLC governance, AI security, threat modeling, vulnerability remediation, incident response, penetration testing, and bug bounty programs. The role combines hands-on software development with executive advising, cross-functional leadership, mentorship, and security risk management across SaaS infrastructure and customer-facing AI products.

Leads payer-focused AI consulting engagements from opportunity discovery through implementation. Builds executive relationships with health plans, identifies AI opportunities, leads proposals and negotiations, shapes scopes and commercial models, and oversees cross-functional delivery. Accountable for client satisfaction, delivery quality, revenue, margin, utilization, pipeline, and measurable business outcomes. Develops repeatable consulting offerings, promotes responsible AI practices, and coaches multidisciplinary teams.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Leads the provider-focused AI solutions portfolio, including roadmap development, commercialization, go-to-market enablement, pricing, partnerships, and performance management. Translates AI research and capabilities into market-ready products that deliver measurable value for healthcare providers. Partners with engineering, operations, finance, legal, compliance, sales, and delivery teams while managing executive stakeholders and cross-functional teams. The role requires extensive experience in AI strategy, healthcare provider domains, consulting, commercialization, partnerships, and enterprise transformation.

Leads the AI solutions portfolio for HR and workforce offerings, including roadmap development, commercialization, go-to-market enablement, pricing, partnerships, client engagement, and performance management. Drives enterprise AI adoption and responsible AI practices while translating research and emerging capabilities into market-ready products. Partners with engineering, sales, operations, finance, legal, compliance, and executive stakeholders to deliver measurable customer and business outcomes.

Leads AI transformation engagements and commercialization for healthcare provider organizations. Advises executives, shapes AI strategies and roadmaps, directs cross-functional delivery, develops client relationships and sales opportunities, and guides responsible AI, workflow integration, pricing, partnerships, adoption, and value realization. The role combines strategic consulting, healthcare transformation, AI-enabled solution development, and business growth leadership.

Leads AI-enabled HR strategy, solution development, commercialization, and client growth. Advises CHROs and senior executives, develops workforce use cases and roadmaps, leads sales pursuits, integrates product, engineering, data science, legal, and compliance teams, and embeds responsible AI, privacy, fairness, and governance into enterprise HR solutions.

Leads the design, development, deployment, and operationalization of enterprise AI/ML, generative AI, and automation solutions. Provides technical leadership across architecture, engineering practices, evaluation, monitoring, governance, security, and responsible AI. Partners with cross-functional stakeholders, mentors engineers, establishes reusable standards, evaluates production readiness, and ensures scalable, reliable, compliant, and cost-effective delivery of AI/ML capabilities.

Coach approximately 20 AI fellows across multiple host organizations through production engineering work. Responsibilities include reviewing pull requests, providing written feedback, conducting 1:1s, leading milestone reviews, delivering curriculum modules, facilitating technical sessions, supporting assessments, identifying cohort-wide issues, and escalating technical or performance risks. The role requires AI-native engineering practices, strong asynchronous communication, and occasional evening sessions across U.S. time zones.

Leads the research, development, and deployment of AI, computer vision, and autonomy technologies for aerospace platforms. Develops navigation, obstacle detection, and other autonomous vehicle capabilities; creates research and technology strategies; transitions solutions into UAV and UAM products; pursues government and internal funding; leads complex R&D programs; and mentors AI engineers.

Design, deploy, and scale responsible AI and machine learning solutions supporting healthcare provider experiences. Lead AI initiatives, provide technical direction to AI engineers, evaluate emerging technologies, and partner with product, data, and business teams. Ensure models meet enterprise standards for performance, security, governance, and scalability while contributing to cloud modernization. The role emphasizes generative AI, LLMs, conversational AI, API development, cloud hosting, and production operations.

Lead end-to-end generative AI and machine learning initiatives, designing scalable and secure AI architectures and developing predictive, prescriptive, optimization, NLP, deep learning, and multimodal models. Analyze healthcare datasets, conduct experiments and A/B tests, evaluate emerging approaches, optimize production systems, and translate findings into executive-level recommendations. The role also emphasizes responsible AI, including fairness, transparency, and accountability.

Develop and optimize full-funnel, multi-channel demand generation campaigns that generate pipeline, accelerate deals, and support cross-sell and upsell opportunities. Partner with product marketing, sales development, content, product, field, partner marketing, and analytics teams. Build lead-nurturing programs, align assets to buyer stages, monitor conversion and ROI metrics, and create dashboards to optimize campaign performance.

The GRC Analyst manages third-party risk assessments, vendor due diligence, security policies, risk analysis, internal audits, and SOC 2 audit support. The role involves maintaining the GRC program, tracking findings, coordinating stakeholders, promoting security awareness, and using AI and machine learning to automate compliance processes. Candidates should have 1–2+ years of relevant experience, strong communication skills, and familiarity with risk methodologies, vendor assessments, policies, and compliance audits.

Develop and support software, automation tools, dashboards, and alarms for cloud infrastructure, cost attribution, and cloud efficiency. Collaborate with cross-functional teams and senior engineers to design reliable systems, APIs, databases, tests, and AI agents. Contribute to architecture and automation strategies while maintaining strong security, communication, and delivery practices.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Develops compliance analytics for AML, sanctions, and consumer compliance programs. Builds data pipelines, dashboards, scorecards, automated reporting, and data quality processes using dbt, GitLab, Python, SQL, Tableau, and Snowflake. Translates regulatory requirements into actionable insights, risk indicators, and metrics while communicating findings to senior management and regulatory stakeholders.