Top Machine Learning Jobs in Minneapolis, MN

Leads complex technology, quality, operations, and transformation projects across multiple business capabilities. Responsibilities include portfolio planning, roadmap development, governance, executive reporting, risk and resource management, business case development, automation and modernization initiatives, process improvement, stakeholder coordination, change management, KPI development, compliance, and mentoring project teams.

Leads consulting engagements transforming healthcare payer systems and applications. Advises executives, assesses architectures and processes, designs technical solutions, and oversees modernization, migration, integration, and implementation programs. Manages scope, budgets, risks, vendors, governance, and multidisciplinary teams while applying Agile methods and identifying responsible AI opportunities. Supports client pursuits, proposals, account growth, service development, and executive communications.

Leads strategic vision, architecture modernization, and delivery of enterprise software engineering solutions. Directs scalable cloud platforms, legacy modernization, AI and machine learning adoption, MLOps governance, and ethical technology practices. Provides executive stakeholder partnership, technical roadmap alignment, engineering team leadership, coaching, hiring strategy, and organizational standards across large-scale healthcare software systems.

Investigate complex AML cases, review transaction-monitoring alerts, determine SAR/STR filing decisions, and communicate findings to regulators, law enforcement, and stakeholders. The role also supports audits, improves AML detection models and typology coverage, analyzes transactional data, identifies financial crime trends, and provides analyst training. Candidates need strong blockchain, AML regulations, investigative writing, and blockchain forensic tool experience, with AI and SQL capabilities preferred or advantageous.

Leads the design, development, deployment, and operationalization of enterprise AI solutions, including LLM applications, RAG systems, intelligent agents, classification models, and decision-support tools. Establishes prompt strategies, guardrails, evaluation frameworks, monitoring, observability, and governance practices. Partners with Finance, Data Engineering, Architecture, Security, and Responsible AI teams to deliver scalable, secure, compliant, and production-ready solutions.

Designs end-to-end architectures for healthcare authorization, referral, and eligibility systems. Partners with stakeholders, product owners, vendors, and engineering teams to define solutions, create architecture diagrams, guide implementation, and enforce scalability, reliability, maintainability, and security standards. Develops AI-powered solutions, evaluates cloud and application technologies, builds proofs of concept, identifies risks, and mentors development teams. Requires substantial healthcare domain experience, modern architecture expertise, API and microservices knowledge, healthcare data standards, and automation or AI experience.

Design, develop, validate, and deploy machine learning, GenAI, LLM, and agentic solutions for enterprise healthcare operations. Build scalable Python inference APIs on Kubernetes, implement semantic search and retrieval capabilities, and maintain AI/ML pipelines. Evaluate emerging technologies, apply responsible AI practices, use AI-assisted development tools, and collaborate with technical and business stakeholders while ensuring strong documentation, coding standards, and performance monitoring.

Leads enterprise AI/ML engineering strategy, architecture, and delivery for AI-ready data and context platforms. Responsibilities include building semantic models, ontologies, knowledge graphs, metadata capabilities, and contextual data products supporting generative AI and agentic workflows. The role directs engineering teams, establishes standards for semantic interoperability and data governance, partners with senior stakeholders, defines platform roadmaps, evaluates emerging technologies, and mentors technical leaders.

Leads enterprise AI/ML engineering teams and defines strategy for AI-ready data and context platforms. Owns semantic architecture, ontologies, knowledge graphs, metadata, data quality, governance, and contextual data products supporting generative AI, intelligent search, decision support, and agentic workflows. Partners with senior stakeholders, translates AI priorities into platform capabilities, evaluates emerging technologies, and mentors technical leaders.

Leads AI/ML engineering teams and defines enterprise strategy for AI-ready data and context platforms. Owns architecture and delivery of semantic models, ontologies, knowledge graphs, metadata capabilities, and contextual data products supporting generative AI, intelligent search, decision support, and agentic workflows. Partners with senior stakeholders on governance, data quality, security, and interoperability while mentoring technical leaders and evaluating emerging technologies.

Own the strategy, roadmap, commercialization, and revenue outcomes for an AI-powered healthcare revenue cycle automation portfolio. Lead pricing, packaging, market analysis, launches, customer adoption, and portfolio performance. Partner with engineering, data science, design, clinical, legal, compliance, sales, and marketing teams to deliver explainable, auditable AI workflows and scale products from concept through multi-customer deployment.

Leads enterprise AI-ready data and context platforms supporting generative AI and agentic workflows. Responsibilities include defining strategy and architecture for semantic models, ontologies, knowledge graphs, metadata, and contextual data products; integrating structured and unstructured data; establishing governance, quality, security, and interoperability standards; partnering with senior stakeholders; evaluating emerging technologies; and leading and mentoring multidisciplinary AI/ML engineering teams.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Develop and deploy data solutions using Palantir Foundry and AIP for client engagements. Lead technical teams, coach team members, analyze system interactions, build applications with large datasets, and apply data engineering and analytics to deliver client outcomes. The role also includes managing client relationships, planning and executing projects, encouraging technology adoption, resolving stakeholder conflicts, and driving continuous improvement.

Leads the development and deployment of data solutions using Palantir Foundry and AIP. Manages engineering teams, coaches team members, oversees project planning and execution, analyzes system interactions, manages client relationships, and drives innovation. The role applies software engineering, data engineering, analytics, and AI/ML techniques to deliver scalable client solutions while maintaining technical and professional standards.

Leads the development and deployment of software and data solutions using Palantir Foundry and AI/ML technologies. Responsibilities include data engineering, analytics, system improvement, client account management, project ownership, team leadership, coaching, stakeholder engagement, and continuous improvement. The role requires building scalable applications with large datasets and delivering customer-focused solutions.

Develop and analyze alternative navigation algorithms and systems for aerospace applications. The role involves integrating sensor-fusion solutions, conducting research and testing, validating navigation performance, and collaborating with multidisciplinary teams. Responsibilities include developing resilient navigation for GPS-denied environments, modeling errors, detecting and mitigating faults, and transitioning research innovations into deployable aerospace products. The position is hybrid in Redmond, Washington, or Plymouth, Minnesota, with no relocation offered.

Own and grow strategic enterprise customer relationships, driving retention, renewals, expansion, and seven-figure software transactions. Develop multi-year account plans, build executive and technical stakeholder relationships, identify expansion opportunities, lead negotiations, maintain forecasts and pipeline visibility, and coordinate cross-functional teams. Engage with data scientists and AI/ML engineers to understand adoption, customer outcomes, and opportunities to expand platform usage across business units and use cases.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

The Data Scientist will partner with Sales, Revenue Operations, and Finance to analyze GTM performance, build and productionize machine learning models, conduct experiments, forecast outcomes, and identify growth opportunities. Responsibilities include statistical analysis, causal inference, Python and SQL development, MLOps, agentic workflow automation, semantic-layer contributions, executive reporting, and communicating insights to nontechnical stakeholders in a fully remote environment.

Leads the design, development, deployment, and monitoring of AI and machine learning models for supply chain decision-making. Extracts and integrates complex data, performs analysis, develops forecasting and optimization solutions, and embeds models into business workflows. Communicates findings to technical and non-technical stakeholders while partnering with business and technology teams to advance AI adoption and deliver measurable impact.

Leads research, analysis, design, development, simulation, and validation of advanced aerospace navigation algorithms and systems. Provides technical direction, mentors engineering teams, shapes technology roadmaps, and integrates sensor-fusion solutions into aerospace platforms. The role emphasizes resilient navigation in GPS-denied environments, regulatory compliance, hardware-in-the-loop testing, high-performance embedded computing, and transitioning research innovations into operational products.

Deploys, configures, optimizes, and supports CrowdStrike Falcon’s AI-powered detection and response capabilities. The role tunes machine learning models, develops security automation playbooks, troubleshoots customer environments, integrates Falcon with existing tools, supports threat hunting and forensic analysis, and develops AI training and customer-facing materials. Requires extensive IT deployment, endpoint, security automation, operating system, AI/ML, scripting, and customer consulting experience, with travel up to 25%.

Leads SailPoint’s global corporate communications function, including corporate narrative, media relations, PR campaigns, crisis communications, executive coaching, podcast strategy, partner communications, and measurement. The role manages internal and agency teams, translates complex cybersecurity and AI concepts into compelling stories, supports product launches and company milestones, builds rapid-response capabilities, and advises executives on reputation and communications strategy.