Top Senior Machine Learning Jobs in Minneapolis, MN

Lead enterprise security operations, resilience, incident response, threat intelligence, cloud security, IAM, and risk management. Serve as deputy to the CISO and primary incident commander while advising executives on cyber risk. Build and scale multidisciplinary security teams, modernize cloud-native defenses, embed security-by-design across products and AI/ML systems, and establish metrics-driven governance, automation, regulatory alignment, and business-focused security strategies.

Senior Product Designer responsible for creating high-craft, 0-to-1 AI recruiting and talent product experiences. The role involves visual and interaction design, rapid iteration, prototyping, design-system development, production-ready delivery, and experimentation with generative AI. Candidates should have strong Figma expertise, exceptional visual design skills, experience shipping SaaS, enterprise, or AI products, and a portfolio demonstrating creative range and execution.

Leads data engineering teams while designing and optimizing scalable batch and real-time data pipelines on cloud platforms. Responsibilities include developing PySpark and Spark workflows, orchestrating Airflow DAGs, managing cloud infrastructure, implementing CI/CD, improving data quality and performance, and mentoring engineers. The role collaborates with clients, product, architecture, and program management teams, while applying generative AI and DevOps practices to improve engineering productivity and operational efficiency.

Design the full Search experience across organic and sponsored results, including typeahead, ranking, filters, empty states, and monetization. Establish design principles and components, partner with product, research, data science, and ML engineering, and use experimentation to improve engagement, relevance, and revenue. The role requires substantial search or discovery design experience, strong product craft, consumer instincts, and comfort designing alongside AI and monetization teams.

Leads Propel America's product and technology strategy, including the Fellow Portal, AI integrations, technology roadmap, software development, Salesforce, infrastructure, data systems, cybersecurity, and vendor relationships. Manages technical staff and outsourced IT providers, oversees architecture, QA, releases, compliance, data privacy, and disaster recovery, and partners cross-functionally to translate organizational needs into scalable products and technology solutions.

Leads enterprise-wide technical and transformation initiatives across Product, Technology, Operations, Data, Security, and Innovation. Responsibilities include program governance, requirements gathering, product documentation, architecture and process modeling, delivery coordination, risk and dependency management, AI use-case evaluation, vendor assessment, and executive stakeholder communication. The role establishes documentation standards and supports modernization through Agile practices, integrations, automation, and responsible AI governance.

Designs and builds data ingestion, feature engineering, analytics, and machine learning pipelines using healthcare and other structured or unstructured data. Develops, tunes, deploys, monitors, and documents predictive models and enterprise data products. Collaborates with data scientists, engineers, product managers, and stakeholders while ensuring data quality, reliability, and production engineering standards.

Develop, train, evaluate, deploy, and monitor machine learning and statistical models using Databricks, Python, SQL, Spark, Delta Lake, and MLflow. Prepare datasets, engineer features, manage model lifecycles, validate data, and support governance practices. Translate client requirements into scalable analytics solutions, analyze trends, and communicate findings to technical and non-technical stakeholders while collaborating across data science, engineering, cloud, security, and business teams.

Build and maintain scalable applications and technology supporting Target’s stores, warehouses, checkout, fulfillment, inventory, and supply chain operations. Design and implement end-to-end functionality, influence architecture, optimize system performance and operational health, troubleshoot issues, and develop distributed systems. Collaborate with engineers, data scientists, project teams, partners, and stakeholders while applying modern programming languages, frameworks, event streaming, databases, monitoring, and machine learning technologies.

The Lead Engineer architects and develops scalable applications supporting Target’s stores, warehouses, checkout, fulfillment, inventory, forecasting, and replenishment systems. The role serves as the technical anchor for a product, owning application architecture, driving architectural improvements, ensuring system performance and operational health, and approving end-to-end functionality. The engineer partners with teams and stakeholders, applies broad expertise across languages and frameworks, and helps leverage data, analytics, and machine learning to improve retail operations.

Own the vision, strategy, roadmap, and outcomes for Augeo’s Incentives product domain. Partner with AI, data science, engineering, and business teams to build ML-driven incentive decisioning, experimentation, personalization, catalog configuration, and automation capabilities. Translate incentive economics and stakeholder needs into prioritized requirements, measure engagement and ROI, ensure privacy and governance compliance, and lead cross-functional planning and delivery.

Build and deploy finance-focused data, analytics, automation, and AI solutions. Partner with FP&A and other Finance teams to identify high-value problems, develop prototypes, create analytical models and dashboards, and apply GenAI, machine learning, APIs, and workflow automation. Scale successful solutions into secure enterprise capabilities while supporting forecasting, planning, reporting, variance analysis, and decision support.

Senior Commercial Counsel will draft, review, and negotiate complex subscription, partnership, vendor, and other commercial agreements. The role primarily supports a global Sales organization, advises cross-functional teams, manages contracts managers, and handles enterprise and strategic partnership transactions. Responsibilities include balancing competing priorities, supporting legal projects, and providing practical, business-minded legal guidance in a fast-paced environment.

Own audience or measurement products for Fetch’s monetization business, translating advertiser goals and purchase behavior into predictive models, datasets, and causal studies. Build and validate audience expansion, measure advertising outcomes, assess bias and uncertainty, and improve products using campaign results. Partner with Product, Engineering, Sales, and GTM, present findings to customers, and develop reproducible analyses and production-ready assets.

Designs, trains, evaluates, and operationalizes intelligent document-processing solutions using OCR, machine learning, LLMs, Python, and cloud data pipelines. Builds extraction, validation, reconciliation, exception-handling, and human-review workflows for sensitive information. Develops secure, auditable, configuration-driven systems with API integrations, monitoring, testing, CI/CD, and infrastructure as code. Partners with business experts to define document fields, quality thresholds, validation rules, and acceptance criteria.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Designs and delivers integrated cloud, AI, and GPU infrastructure solutions for strategic technology partners. Responsibilities include architecting integrations, building production-grade reference implementations, defining networking and security patterns, enabling partner engineering teams, supporting customer deployments, troubleshooting complex environments, and translating partner feedback into product roadmap requirements. The role requires deep Kubernetes, Terraform, Python, AI inference, integration architecture, and cloud infrastructure expertise.

Leads the launch of BGO’s enterprise sales motion for its AI-first data operations proposition. Responsibilities include developing prospecting strategy and sales playbooks, generating new-logo pipeline, selling complex $1M+ enterprise solutions, building executive relationships, closing transformational deals, supporting AI/ML product integration, and representing the company at industry events. The role partners with marketing, communications, client solutions, and leadership on RFPs, product roadmap development, and strategic market initiatives.

Own technical wins for strategic enterprise sales, partnering with Account Executives to discover customer needs and develop production-ready solutions. Build proofs of concept, demonstrations, prototype AI agents, and supporting tools while engaging AI teams, data platform teams, and enterprise architects. Apply hands-on experience with LLMs, agents, data science, machine learning, or data engineering to explain how agents retrieve data and use business context.

Build and deploy enterprise agentic AI solutions, including agents, MCP tools, plugins, orchestration architectures, evaluation harnesses, and secure APIs. Integrate agents with search and collaboration platforms, instrument production behavior, manage cost and latency, and test against prompt injection and tool vulnerabilities. The role requires backend software engineering, production agent development, MCP experience, LLM evaluation, and AI coding assistant expertise, with preferred experience in managed runtimes, retrieval systems, and enterprise security.

Lead development and deployment of an agentic AI/ML pipeline for identifying, prioritizing, and pricing high-cost healthcare claims. Responsibilities include model development, confidence scoring, HITL safety design, ML lifecycle management, monitoring, workflow automation, responsible AI, and enterprise-scale analytics using Databricks and Snowflake. The role also evaluates emerging AI technologies and supports regulatory-aware automation and healthcare data transformation.

Designs, deploys, and scales AI and machine learning solutions for enterprise healthcare applications. Responsibilities include building and tuning production models, developing MLOps frameworks and deployment pipelines, monitoring model performance, automating workflows, evaluating emerging AI technologies, and ensuring security, scalability, responsible AI, and governance standards. The role collaborates with software engineers, data scientists, and business stakeholders.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

Leads cyber risk assurance strategy and multidisciplinary teams responsible for control monitoring, testing, evidence management, issue remediation, audit support, regulatory readiness, and assurance automation. The role advances continuous, AI-enabled assurance by translating regulatory and cybersecurity requirements into measurable outcomes, maintaining assurance frameworks, evaluating control effectiveness, managing concurrent activities, and reporting metrics to support executive risk decisions.

Own and negotiate complex commercial transactions, including customer agreements, research collaborations, partnerships, data licenses, SaaS contracts, vendor agreements, and professional services agreements. Partner with sales, science, finance, and R&D teams, particularly on life sciences and computational chemistry deals. Build scalable legal infrastructure through playbooks, templates, fallback positions, self-service processes, and AI-enabled contract workflows.