Top Senior Machine Learning Jobs in Milwaukee, WI

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

Own the strategy, requirements, evaluation, and execution of AI agent products and systems. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define evaluation frameworks, drive prioritization, and ensure AI features are understandable, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions and reliable real-world workflows.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define offline and online evaluation frameworks, drive product execution, and ensure AI features are correct, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions, roadmaps, and rapid iteration.

The Senior Product Architect will design security products, collaborating with product management and engineering teams, focusing on architecture and functionality for high-level product features.

Lead the Data Sources product roadmap for document parsing, fraud detection, and bank aggregation. Drive metrics (parse accuracy, fraud catch rate, connection success, SLAs), write specs, engage clients, mentor PMs/engineers, and represent the platform externally. Prioritize document types, extraction models, reliability, and scalability to improve conversion, client satisfaction, and operational efficiency across mortgage, tenant screening, and government use cases.

Lead integrated paid media strategy and execution across channels, modernize media planning with technology and data, manage agency/vendor relationships and multimillion-dollar budgets, build media capabilities and teams, and deliver executive insights to optimize ROI using AI, automation, and advanced measurement.

Lead a centralized Data Science & Engineering team to build scalable data pipelines, productionize ML/AI solutions, ensure data governance and reliability, partner with cross-functional stakeholders to prioritize initiatives, and drive platform improvements for analytics, personalization, and product features.

Provides strategic and technical leadership for Lilly’s eDiscovery program across the full EDRM lifecycle. Manages legal hold systems, data preservation and collection, processing, review, production, vendor relationships, workflows, and chain-of-custody requirements. Evaluates AI, machine learning, TAR/CAL, predictive coding, and analytics solutions while ensuring defensible legal processes. Partners with Legal, Privacy, Records Management, IT, Compliance, Cybersecurity, outside counsel, and business stakeholders, and mentors team members.

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

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.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Build and deploy production-grade LLM applications, AI agents, models, and scalable RAG pipelines for investment and business workflows. Architect secure MCP integrations with enterprise systems, establish MLOps and LLMOps practices, optimize model performance and latency, and develop evaluation, monitoring, governance, and rollback processes. Collaborate with data engineering and platform teams to provide secure, governed access to organizational data.

Lead development of safety frameworks and V&V for end-to-end autonomous robotics, perform risk assessments and safety reviews, derive technical safety requirements, and coordinate cross-functional teams to monitor fleet performance and deploy scalable autonomy.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

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

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 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.

Develop and expand software products and platforms across backend, frontend, cloud, AI, and machine learning systems. Build efficient, reliable, and testable code; collaborate with business partners to launch features; influence product and engineering decisions; mentor team members; and help shape team culture and product vision in an agile environment.

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.