Top Senior Machine Learning Jobs in Milwaukee, WI

Lead divisional FP&A including monthly/quarterly forecasting, annual planning, SG&A and SKU-level profitability analysis. Partner with commercial, supply chain, operations and product teams to drive cost reduction, forecast accuracy, inventory rightsizing, and strategic initiatives. Promote systems and process improvements, automation and analytics to support executive decision-making.

Design, build, and deploy AI-powered data automation workflows to replace manual data quality and enrichment processes. Integrate third-party enrichment platforms, implement monitoring and governance, define quality metrics, and enable self-service automation across CRM, marketing, and sales data to improve accuracy and efficiency.

Own product strategy, vision, roadmaps, backlogs, and delivery for enterprise SaaS products serving financial services organizations. Translate strategy into requirements and user stories, lead Agile ceremonies, engage customers, monitor product metrics, manage delivery risks, and align portfolio companies with leadership and cross-functional teams. Identify and deliver AI-enabled capabilities, workflow automation, analytics, and intelligent business solutions.

Pre-sales technical role: demonstrate Kore.ai platform, architect and whiteboard solutions, run use-case workshops, estimate ML effort, collaborate with product and delivery teams, and support sales to close enterprise AI and contact-center deals.

Lead pet insurance pricing and state rating plans; build and integrate ML rating models; design pricing strategy for expansion; support rate filings; partner with Data Science, Underwriting, and Finance; and manage and grow an actuarial analyst team.

Serve as the primary product contact embedded with health system clients to discover workflows, design AI-powered solutions, scope pilots, and lead 0→1 deployments. Translate clinical and administrative workflows into product requirements, drive UAT and go-live, measure business success metrics, and surface field insights into the product roadmap. Travel to client sites for discovery and deployment support and collaborate with ML engineers, FDEs, and solution teams to ensure measurable ROI and expansion.

Own a Pod's product roadmap: discover customer problems, define initiatives, write high-level requirements, partner with engineering, integrate AI-driven workflows, ensure adoption, track outcomes, and steward product metrics.

Build and productionize customer-facing data and AI solutions on the Databricks platform. Own architecture and design decisions, develop end-to-end data pipelines and applications, integrate machine learning models, and guide enterprise customers through implementation and adoption. Collaborate with engineering, product, support, project managers, and customer stakeholders while delivering projects, documenting solutions, resolving issues, and creating reusable frameworks. Travel to customers approximately 20% of the time.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Responsibilities include managing product backlogs and roadmaps, prioritizing features, defining requirements and success metrics, coordinating cross-functional engineering, AI, UX, data, and architecture teams, leading product discovery and release planning, monitoring adoption and KPIs, and ensuring alignment with product governance, architecture, and Responsible AI standards.

Design, build, and integrate AI-enabled applications using C#/.NET and Azure. Develop data ingestion, transformation, and automation pipelines for structured and unstructured data. Implement and optimize LLM/Generative AI solutions, build APIs, and support end-to-end delivery from design through production handoff while partnering with business stakeholders.

Develop and deploy deep learning models for AI-guided antibody drug discovery and target identification. Design experiments, build systems biology models, and create in silico and in vitro validation approaches. Collaborate with biological and wet-lab teams, present findings, publish high-impact research, and mentor scientists and engineers.

Leads engineering managers and software teams building customer-facing front-end applications and internal and external APIs. Sets technical direction, oversees delivery, manages risks and dependencies, improves engineering quality and security, develops talent, supports hiring, and partners with product and design. The role drives innovation and scalable software solutions for connected vehicle and fleet operations.

Leads the engineering strategy, architecture, development, operations, and continuous improvement of an enterprise agentic AI foundation. Establishes scalable engineering standards, operating models, governance, and reusable platform services that enable AI products and intelligent workflows. Partners with product, data, infrastructure, security, and business teams to modernize existing systems, guide cross-functional delivery, monitor operations, and communicate priorities, risks, and investment needs to senior leaders. Manages and develops product or engineering leaders while driving measurable business value.

Lead strategy and roadmap for Brain Health & Detection, drive AI/ML-powered detection and anomaly systems, partner with engineering and data science, set success metrics, and lead end-to-end product execution and adoption for scalable service health intelligence.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

Design and scale fraud-mitigation strategies for buyer, seller, and account fraud across Stripe products. Monitor portfolios, identify and predict risky behavior, propose controls, automate workflows, collaborate with Product/Engineering/Data Science, and educate users to minimize losses while enabling growth.

Lead data science for Root's digital partnerships channel, managing a team to drive growth, profitability, experimentation, forecasting, optimization, and measurement. Partner with cross-functional teams to improve acquisition economics, influence product and technical roadmaps, deliver executive reporting, and establish scalable operating processes.

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

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.

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.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.