Top Senior Machine Learning Jobs in Minneapolis, MN

Design, develop, deploy, and maintain scalable detections across SIEM, EDR, cloud, identity, and network platforms. Translate threat intelligence and incident findings into high-fidelity detection logic, validate coverage against MITRE ATT&CK, measure detection performance, and collaborate with intelligence, IR, hunting, and platform teams to close visibility gaps and automate detection workflows.

Lead development and operationalization of a clinical reasoning framework for trustworthy clinical AI. Partner with product, engineering, editorial, and design to define decision pathways, evaluation benchmarks, validation protocols, and ongoing expert review. Translate clinical feedback into AI system improvements, represent the team externally, and optionally maintain limited clinical practice.

As a Senior AI/ML Engineer, you will design and build end-to-end ML systems, manage ML lifecycle workflows, and ensure compliance with AI standards within the healthcare sector.

Lead hands-on development and deployment of AI/ML solutions and rapid prototypes (with emphasis on Generative AI/LLMs), embed responsible AI practices, integrate AI into engineering workflows, and scale successful pilots across the enterprise while collaborating with cross-functional leaders.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Develop and evaluate novel AI/ML solutions for healthcare using structured and unstructured data. Build and test deep learning and classical ML models, design experiments, perform statistical analysis and visualizations, document models, collaborate with stakeholders, RUAI, and engineering to productionize solutions and MLOps pipelines, and publish/patent research.

Lead end-to-end design, implementation, deployment, and operation of production AI/ML-enabled full-stack applications. Build LLM-powered features, design scalable backend services and data models, deploy on Azure, implement CI/CD and observability, and mentor engineers while ensuring secure, compliant integration into clinical workflows.

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

Design, build, deploy, monitor, and optimize unattended Power Automate RPA workflows. Collaborate with business and IT partners, ensure compliance and security, document solutions, perform testing and code reviews, support production, and cross-train on Automation Anywhere.

Lead the AI/ML Engineering team to transform healthcare claims processing, driving automation and operational intelligence across claims systems.

Drive supply chain efficiency through data analytics, KPI development, process redesign, ERP/WMS/automation selection and implementation, Lean Six Sigma continuous improvement, AI-driven forecasting, cross-functional project leadership, audits, and change management with suppliers and 3PLs.

Designs and conducts statistical analyses for observational and interventional health research, contributes to grant proposals and publications, consults with clinicians, develops analysis plans, and builds an independent externally funded research program while collaborating across multidisciplinary teams.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead product strategy and execution for a B2B SaaS marketing analytics platform. Translate research into requirements, own the backlog, partner with engineering and GTM, define success metrics, and ship API- and data-heavy features for technical users.

The Senior Director of AI Insights leads AI-driven data insights to enhance decision-making and strategy alignments across the organization, fostering stakeholder engagement and AI literacy.

The Senior Scientist will design small molecules using computational tools, lead projects, manage external teams, and collaborate with machine learning and medicinal chemistry teams.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Lead and own cross-organizational technical programs for ML and robotics platform development, define roadmaps and milestones, remove blockers, align diverse engineering teams, and drive adoption of platform best practices to deliver scalable autonomy and infrastructure outcomes.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

Lead consolidation of customer email and SMS into a centralized CRM (Braze), design and optimize multi-channel customer journeys, manage deliverability and sender reputation, build segmentation and experimentation frameworks, partner cross-functionally to implement integrations and measure campaign performance.

Own end-to-end product development for AI/ML revenue cycle solutions: define vision and roadmap, write specs and user stories, prioritize backlog, work closely with data scientists and engineers, drive agile delivery, ensure quality, and measure product performance with stakeholders.

Provide legal counsel on privacy, AI, identity, and advertising technology; embed privacy by design with product and engineering teams; draft and negotiate privacy provisions and DPAs; advise on cross-border transfers and SCCs; run privacy and AI risk assessments; support incident response; create scalable legal playbooks and AI-enabled workflows; represent Yahoo in industry standards bodies.

Lead technical direction and delivery of ML platform infrastructure (feature store, model serving, experimentation, training pipelines). Drive architecture, resolve system-level issues, write production code, mentor engineers, and partner with ML, data, and product teams to enable scalable, reliable ML model development and deployment.