Top Senior Machine Learning Jobs in Minneapolis, MN

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.

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.

Build and deploy production-grade LLM agents and RAG pipelines that detect, triage, and remediate platform and application issues. Design orchestration, tool calling, guardrails, evaluation frameworks, observability integrations, and secure AI infrastructure. Optimize prompts, models, retrieval, cost, latency, and quality while partnering with SRE, InfoSec, and platform teams. Develop APIs, testing workflows, and reusable enterprise AI components.

Build and lead production AI/ML, Generative AI, and data engineering solutions for healthcare analytics and patient safety platforms. Develop full-stack applications, microservices, APIs, data pipelines, dashboards, self-service analytics, RAG systems, and event-driven architectures using cloud-native technologies. Apply engineering best practices including testing, CI/CD, observability, security, and performance optimization. Mentor engineers, lead technical initiatives, and collaborate with product, analytics, business, and platform teams.

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.

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.

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.

Design, develop, and deploy secure AI/ML and full-stack solutions for healthcare underwriting and benefits modernization. Build RAG pipelines, integrate LLMs and agentic AI capabilities, develop Python-based machine learning systems, and expose models through production APIs. Collaborate with engineering, architecture, product, data, and underwriting teams while ensuring model availability, security, performance, testing, monitoring, and responsible AI use.

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.

Designs, builds, and scales enterprise AI applications using classical machine learning, generative AI, RAG, and agentic architectures. Develops intelligent workflows, autonomous agents, knowledge systems, chatbots, copilots, and decision-support solutions integrated with enterprise platforms and APIs. Leads AI governance, evaluation, observability, security, and human-in-the-loop controls while advising clients on enterprise AI transformation. Requires extensive experience with Claude, OpenAI, LLMs, cloud platforms, vector databases, semantic search, and production-grade AI implementations.

Leads an AI/ML engineering team responsible for enterprise connectors, plugins, MCP servers, and integrations across Microsoft, OpenAI, Anthropic, and Google platforms. Oversees team development, intake, technical quality, secure configuration, governance reviews, testing, release readiness, operations, incident response, vendor partnerships, and continuous improvement. Partners with product, business, architecture, security, legal, privacy, identity, and platform teams to deliver reliable, auditable AI integration services.

Leads Vizient’s indirect spend data and analytics strategy, operating model, governance, quality standards, reporting, automation, and AI adoption. Oversees data lifecycle management, modeling, integration, categorization, normalization, analytical methodologies, dashboards, and decision-support tools. Manages data and analytics teams, develops reusable assets for consulting engagements, partners with technology and product teams, and supports business development and member presentations.

Designs and implements AI and automation solutions for HR by translating business needs into technical requirements, user journeys, prototypes, test plans, and scalable experiences. Leads UAT, documentation, performance monitoring, troubleshooting, and continuous improvement while partnering with HR stakeholders, technology teams, architects, developers, data scientists, and vendors. The onsite Minneapolis role requires up to 10% travel and experience with enterprise AI, automation, or chatbot implementations.

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 the vision, strategy, roadmap, development, and enhancement of telematics web and mobile applications. Responsibilities include prioritizing product backlogs, translating requirements into user stories, coordinating cross-functional teams, managing stakeholders, collaborating on UX, monitoring KPIs, analyzing feedback, and overseeing products through launch and optimization. The role requires enterprise application, telematics, fleet management, transportation, application development, and Agile/Scrum experience.

Develop and deploy predictive and prescriptive maintenance, anomaly detection, and machine learning models for industrial IoT applications. Own the full data science lifecycle, including scoping, exploratory analysis, model development, tuning, testing, deployment, and monitoring. Collaborate with engineers and Data Ops, apply models to high-volume time-series data, identify organizational opportunities, and mentor team members.

Leads the global AI and digital transformation strategy for customer care and order operations. Owns multi-year roadmaps, customer-facing digital platform priorities, process automation, AI governance, and value realization. Partners with Digital, IT, Data, Commercial, Supply Chain, and customer-facing teams to deliver scalable capabilities, improve customer and employee experiences, modernize order-to-cash operations, and drive enterprise adoption. Requires executive influence, large-scale transformation leadership, organizational change expertise, and extensive managerial experience.

Defines enterprise architecture, strategy, standards, and roadmaps for SAP Master Data Governance and master data management. Leads SAP MDG integrations with S/4HANA, ECC, BTP, data platforms, and third-party applications. Translates business requirements into scalable solutions, guides implementations and deployments, develops prototypes, and provides technical leadership for data conversions, cutovers, production issues, and transformation initiatives.

Supports transcatheter heart valve technology development through cardiovascular imaging analysis, anatomical reconstruction, segmentation, predictive modeling, and device-anatomy assessment. Develops Python and MATLAB tools, analyzes clinical and preclinical datasets, contributes to technical investigations and research documentation, and partners with engineering, clinical, scientific, physician, and external research teams. The role requires expertise in cardiac anatomy and structural heart disease and is based primarily onsite in Mounds View, Minnesota, with up to 10% travel.

Leads imaging analysis, anatomical reconstruction, computational modeling, and predictive assessment for transcatheter heart valve technologies. Develops Python and MATLAB workflows, evaluates device-anatomy interactions, analyzes cardiovascular imaging datasets, and supports product development, preclinical studies, and research. Collaborates with engineering, clinical, scientific, physician, and research teams while producing technical documentation and providing mentorship in cardiovascular imaging and modeling.

As a Lead Applied Scientist, you will define research strategy, mentor teams, and innovate AI/ML solutions for legal and other professional sectors.

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.

Leads globally distributed software engineering teams delivering strategic healthcare, payment integrity, AI, and enterprise platform initiatives. Defines roadmaps, manages execution governance, operationalizes AI/ML and Generative AI capabilities, promotes responsible AI, and drives cloud architecture, DevOps, CI/CD, SRE, release management, and production operations. Partners with product, business, architecture, and executive stakeholders while monitoring delivery metrics and developing engineering talent.