Top Senior Machine Learning Jobs in Milwaukee, WI

The Staff Algorithm Engineer designs, validates, and implements ECG algorithms for medical devices, ensuring they meet clinical and performance standards while complying with quality regulations.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.

The Senior Product Manager will lead the integration of airline and third-party partners, optimize supply metrics, and leverage AI for automation. Responsibilities include managing APIs, collaborating with engineering, and improving the booking experience.

The Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The VP of Sales will drive enterprise adoption of AI-powered healthcare software, engage with stakeholders, and shape go-to-market strategies for new AI products.

As a Machine Learning Engineer, you'll design, build, and maintain models to detect security threats, ensuring model efficiency and aligning initiatives with business goals.

Lead the vision and strategy for the Commerce Intelligence Platform, transforming data assets into scalable, revenue-generating products, fostering cross-functional collaboration and driving market growth.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

Lead end-to-end IFS Cloud architecture and integrations, design AI-augmented solutions (forecasting, scheduling, anomaly detection), define extension and environment strategies, ensure security/resilience, and align IFS data with enterprise BI/ML initiatives while partnering with stakeholders.

Lead the Performance ML team at MNTN, driving strategy and deployment of predictive models for ad technology, while managing, mentoring, and scaling engineering teams.

Lead delivery of advanced analytics and investigative support for federal programs. Manage multiple concurrent projects, schedules, costs, risks, personnel, vendors, and stakeholder communications to ensure quality, timely contract-aligned deliverables.

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.

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.

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.

Embed with customers to discover needs, design and implement production-grade integrations (APIs, data pipelines, event-driven workflows), deploy and troubleshoot solutions, train IT teams, and drive adoption and measurable business outcomes.

The Enterprise Account Executive will drive revenue growth by managing complex sales cycles, closing deals with Fortune 500 companies, and understanding both technical and business needs.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Lead technical solution development for military and Federal civilian health capture and proposal efforts, ensuring technical compliance and producing quality architecture designs.

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.

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.