Top Remote Machine Learning Jobs in Minneapolis, MN

Lead product strategy, roadmap, and delivery for Falcon Complete’s internal MDR tooling, including AI-powered investigation and triage, ticketing, case management, and analyst workbench systems. Partner with security operations, analysts, engineering, and data science teams to translate workflows into product requirements, prioritize automation, improve analyst productivity and response times, define success metrics, and enhance customer outcomes.

Develop and implement data science strategies for machine learning applications including lead scoring, churn modeling, pricing, personalization, and fraud detection. Own end-to-end initiatives spanning data analysis, feature engineering, model training, inference, and monitoring. Collaborate with engineering, infrastructure, analytics, and business teams to deliver measurable impact, improve data capabilities, and communicate findings to technical and non-technical stakeholders.

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.

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.

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 technical pre-sales for Fortinet’s AI security solutions, supporting discovery, architecture reviews, demonstrations, proofs of concept, deployments, partner enablement, and customer training. The role requires deep knowledge of AI technologies, cloud platforms, containers, Kubernetes, and AI security practices. It also supports sales strategy, technical handoffs, customer relationships, and evangelism while traveling up to 50%.

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 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.

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.

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.

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.

Leads architecture and hands-on delivery of production-grade software, machine learning, generative AI, RAG, and AI-agent solutions. Builds cloud-native services, APIs, data integrations, MLOps/LLMOps pipelines, evaluation frameworks, and secure deployment patterns. Owns technical initiatives from experimentation through production, including reliability, observability, testing, incident resolution, responsible AI, and cost optimization. Influences cross-team architecture and roadmaps while mentoring engineers without direct management responsibilities.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Lead product strategy, roadmap execution, and measurable outcomes for an AI-enabled refinance title decisioning platform. Translate strategy into requirements, user stories, and acceptance criteria; prioritize initiatives against OKRs; and partner with engineering, data science, operations, sales, and marketing. Monitor product health, accuracy, costs, service levels, and performance through metrics and dashboards. Manage stakeholders, customer onboarding, continuous improvement, and automation opportunities across a regulated real estate workflow.

Own and scale Tilt’s credit card acquisition through affiliate partnerships, paid search, and paid social. Lead channel strategy, partner launches, targeting, experimentation, and optimization while collaborating with credit, data science, product, engineering, and marketing. Use SQL and Python to evaluate funnel performance, unit economics, approvals, activation, spend, and credit outcomes. Shape acquisition policies and application experiences to drive profitable growth.

Leads the strategy, technical direction, and delivery of insurance data science across pricing, underwriting, cost modeling, demand modeling, and growth. Oversees predictive modeling standards, model lifecycle governance, engineering collaboration, regulatory alignment, and production deployment. Builds and develops a high-performing data science organization while partnering with actuarial, product, underwriting, pricing, and executive leadership to connect analytical work with profitability and business outcomes.

Designs and governs enterprise data integration and digital platform architecture. The role establishes scalable ingestion, transformation, interoperability, cloud, governance, security, and data quality frameworks for customer data. It integrates healthcare and enterprise systems using HL7, FHIR, DICOM, APIs, and modern data architectures, while enabling analytics, machine learning, and decision intelligence. The architect provides cross-functional technical leadership, advises customer onboarding initiatives, partners with Product and Engineering, and mentors technical teams. The position requires 50% travel.

Designs, deploys, and maintains AI and machine learning solutions, including generative AI, LLM, RAG, and conversational AI applications. Owns agentic engineering infrastructure, application guardrails for patient-care workflows, data pipelines, analytics, model governance, monitoring, and cloud deployment. Provides architectural leadership, improves engineering throughput, ensures privacy and compliance, and translates business needs into scalable AI solutions.

Designs, implements, and maintains automated security detection, orchestration, and integration capabilities for USPS. Analyzes security telemetry, identifies anomalies and detection gaps, enhances detection content, validates workflows, and supports SOC, threat intelligence, and incident response teams. The role also translates operational needs into technical solutions, researches emerging security and machine-learning capabilities, and maintains documentation, runbooks, and procedures.

Lead product positioning, go-to-market strategy, launches, customer insights, competitive intelligence, messaging, sales enablement, and thought leadership for AI-driven cybersecurity and authentication products. Translate complex AI and machine learning technologies for technical and business audiences, manage marketing plans and budgets, support customer case studies, and mentor a high-performing product marketing team. Partner closely with Product, Engineering, Sales, Marketing, and executive leadership.

Supports development of data pipelines, AI and machine learning components, and product features. Writes and tests Python and SQL, performs data quality checks, troubleshooting, documentation, and evaluation, and participates in code reviews and product pod discussions under engineer guidance.