Top Machine Learning Jobs in Madison, WI

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead vision, strategy, and roadmap for Fetch's referral growth engine. Own end-to-end referral lifecycle, build incentives, experimentation, AI-driven personalization, and cross-functional initiatives to drive MAU growth and durable network effects.

Manage a portfolio of SaaS customers, build relationships, monitor usage, prevent churn, handle support and troubleshooting, identify upsell/renewal opportunities, and relay customer feedback to product and engineering.

Senior product engineer owning end-to-end product surfaces for a computer vision platform. Ship features from idea to production, prioritize roadmap, design UX details, integrate APIs, improve annotation and model-assisted labeling, and collaborate with engineering and users to drive product impact.

Design, develop, and evaluate conversational AI agents and generative AI products. Collaborate with AI scientists, ML engineers, and Responsible AI/Model Validation teams to ensure state-of-the-art, ethical solutions and support deployment and integration of conversational systems.

The Director, Strategy & Insights will enhance client performance using advanced analytics and machine learning, ensuring client satisfaction and achieving revenue goals through strategic planning and cross-functional collaboration.

The Solutions Engineer will provide technical support for customers, ensure satisfaction, communicate with sales, and analyze customer needs for product enhancements.

As the Engineering Lead, you will guide product strategy, manage and mentor engineers, and ensure successful execution in product areas, focusing on machine learning and technical expertise across teams.

The Product Manager will lead product development, working with cross-functional teams, driving growth, and creating user experience frameworks.

The role focuses on leading editorial efforts to define industry narratives around energy infrastructure, translating regulatory changes into strategic content for executives, and influencing sales and positioning through high-impact communications.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

The Head of AI will define and execute an AI roadmap, lead research initiatives, mentor the AI team, and collaborate with senior leadership to enhance health technology.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Chief Architect will lead the technical direction for Legion's Workforce Management platform, focusing on architecture decisions, AI systems, and scalable software solutions. Responsibilities include hands-on coding, technical leadership, and ensuring systems meet enterprise standards for performance and security.

Senior product leader setting the multi-year Applied Intelligence vision and roadmap for AI-powered B2B AR products. Own end-to-end AI product lifecycle, governance, evaluation standards, talent building, cross-functional partnership, and external representation to drive commercial impact and customer adoption.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

Define and execute Americas logistics and warehousing strategy; lead multi-site DC operations, inbound/outbound logistics, carrier management, trade compliance/imports, P&L oversight, WMS/TMS/ERP optimization, and AI/automation adoption. Requires cross-regional enablement and ~25-40% travel.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

Design and run partner presales enablement programs that build hands-on technical proficiency across ISV and C&SI partners. Own curriculum, assessments, roadmaps, KPIs, and large-scale learning events; coach trainers; align cross-functionally to drive partner-sourced pipeline and certification outcomes.

Lead operationalization of AI strategy by implementing scalable AI platforms, standards, and governance. Identify and prioritize high-impact AI and analytics use cases, drive end-to-end delivery into production, embed AI into business processes, manage AI teams, mentor practitioners, and evaluate emerging AI/GenAI technologies to ensure responsible, secure, and measurable business impact.