Top Machine Learning Jobs in Milwaukee, WI

Leads the design, development, deployment, and optimization of generative AI and machine learning solutions. Architects agentic LLM workflows, integrates AI with enterprise systems, performs data engineering and analysis, and applies secure software practices for production deployment. Develops reusable AI frameworks, implements responsible AI controls, communicates technical concepts to stakeholders, and mentors engineers and data scientists. The role requires expertise in LLMs, RAG, prompt engineering, fine-tuning, model evaluation, and AI governance.

Design, train, and productionize machine learning models for fraud and identity risk across the full ML lifecycle. Research new fraud types, perform feature engineering and labeling, write production-ready code for real-time decisioning, monitor models, and provide analyses to inform product, sales, and data acquisition.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

The Enterprise Account Executive drives revenue through high-value contracts, managing complex sales processes and relationships with executive stakeholders in financial services.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Lead assessment, redesign, and hands-on implementation of data pipelines, ML workflows, and platform infrastructure. Produce prioritized system designs, harden production pipelines, improve observability, reliability, and data quality, and mentor the data team.

Build and ship production LLM-powered agents, workflows, and integrations using platform templates, pipelines, and guardrails. Develop comprehensive evaluation suites, integrate business systems and data sources, instrument cost and quality telemetry, and collaborate with business users to iterate within defined scopes. Requires extensive software engineering experience, production LLM application expertise, strong Python and TypeScript skills, API craftsmanship, prompt and context engineering, and a commitment to guardrails and evaluation.

Build and deploy LLM-powered agents, workflows, and integrations using production templates, pipelines, and guardrails. Develop comprehensive evaluation suites, integrate with business systems and data sources, and instrument solutions for cost and quality telemetry. Collaborate with business users to iterate rapidly within defined scopes. The role requires strong Python and TypeScript skills, production LLM application experience, API development, prompt and context engineering, and retrieval expertise.

Build and deploy LLM-powered agents and workflows using production templates, pipelines, and guardrails. Develop comprehensive evaluations, integrate AI systems with business data sources, and instrument cost and quality telemetry. Collaborate with business users to rapidly iterate within defined scopes while maintaining production standards. The role requires extensive software engineering experience, production LLM application development, strong Python and TypeScript skills, API expertise, and retrieval or healthcare data experience as desirable qualifications.

Build and deploy LLM-powered agents and workflows using production templates, pipelines, and guardrails. Develop comprehensive evaluations, integrate with business systems and data sources, instrument cost and quality telemetry, and collaborate with business users to iterate within defined scopes. The role requires strong Python and TypeScript skills, production experience with agents, RAG, and tool use, as well as expertise in prompt and context engineering.

Develops AI/ML prototypes, APIs, microservices, integrations, and lightweight user interfaces for federal and DoD-aligned mission workflows. The role integrates and optimizes machine learning models for dashboards and applications, supports data ingestion and preprocessing, validates performance, and helps transition models into production. Collaboration with data scientists, architects, developers, PMO leadership, and cybersecurity teams is required. The position requires five years of relevant experience, a bachelor’s degree, ITIL v4 Foundation certification, and Public Trust or active Secret clearance.

Designs AI/ML pilots, predictive analytics and anomaly detection models, behavioral analytics, content classification, personalization algorithms, and end-to-end machine learning pipelines. Develops prototypes and production-ready solutions, evaluates AI technologies, supports experimentation, integrates ML insights into dashboards, and ensures model governance, explainability, bias mitigation, accuracy, and security compliance in federal and DoD-aligned environments.

Lead go-to-market and partner development for Personal Loans and Point-of-Sale products. Own end-to-end enterprise sales, build C-level relationships, close complex deals, and coordinate cross-functional teams to launch AI-driven consumer lending integrations and scale market presence.

Author and verify rigorous multiple-choice computer science assessment items across many CS domains to create gold-standard benchmarks for AI research. Produce correct answers, nine plausible distractors, solution explanations, difficulty labels, and authoritative references. Review and edit questions for technical accuracy, clarity, and reproducibility. Contribute asynchronously as an independent contractor, ~10+ hours/week, fully remote.

Develop, deploy, and optimize scalable machine learning solutions, including predictive models, deep learning systems, data pipelines, and model-serving infrastructure. Monitor model performance, manage retraining and lifecycle processes, ensure quality and compliance, and support responsible AI practices. Collaborate with data scientists, engineers, product teams, and business stakeholders while researching emerging AI technologies and improving AI architectures.

Leads the architecture, development, deployment, and optimization of enterprise machine learning solutions. Responsibilities include designing scalable ML systems, developing predictive models, supporting MLOps and model lifecycle management, improving data quality and feature engineering, implementing governance and validation frameworks, and mentoring technical teams. The role also contributes to AI strategy, innovation initiatives, responsible AI practices, and organizational modernization.

Define and execute the product roadmap for AI-driven on-chain monitoring tools to detect blockchain threats. Collaborate with engineering, research, and stakeholders, analyze market and customer feedback, prioritize features, ensure timely delivery, and maintain transparent communication across teams.

Lead a global manufacturing engineering organization to standardize processes, drive lean continuous improvement, deploy automation and Industry 4.0 solutions (cobots, ML), and ensure safety, traceability, and zero-defect customer quality across international sites.

Lead security engineering for an AI-native cybersecurity product: architect product security, build and evolve operational security and incident response, collaborate with ML engineers to integrate security into AI agents, implement protections and automation, and represent Cogent externally through writing and speaking.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

Partner with a retained search firm to place software engineers and quant developers at top hedge funds. Provide candidate flow from your network; firm supplies clients, process, and fees. Remote, commission-only role with placement and pipeline incentives. Apply with placement examples, outreach metrics, and a candidate submission.

Own and close the company’s largest, most complex public-sector enterprise deals. Prospect and grow territory, navigate multi-stakeholder procurement, manage forecasting and pipeline, expand revenue within major accounts, and mentor Account Executives by providing strategic deal support and operational leadership.

Lead technical strategy and hands-on engineering for Airbnb's AI-powered ads growth engine. Architect scalable systems for creative generation, bidding, budget optimization, and audience management across paid channels. Write and review code, set standards for availability and quality, collaborate with Marketing/Product/ML teams, roll out staged automation, and mentor engineers to advance platform autonomy while ensuring brand safety and human-in-the-loop controls.

Lead and align ML, data, and engineering teams to define multi-year AI roadmaps, deliver production ML solutions, ensure robust data pipelines, set success metrics tied to business outcomes, and grow/mentor senior managers and engineers.