Top Senior Machine Learning Jobs in Milwaukee, WI

Lead end-to-end product design for an AI-powered women’s health platform. Responsibilities include defining UX vision, creating interaction models, information architecture, wireframes, high-fidelity interfaces, prototypes, design systems, and user research. Collaborate with product, engineering, ML, marketing, and leadership teams to translate business needs into customer-focused solutions, manage design initiatives, and measure product success through user feedback and metrics.

Leads the transformation of Sophos’s pricing operations by building a centralized function, establishing pricing governance and review cadences, developing AI-assisted competitive and discount analysis capabilities, and aligning pricing across SecOps and Network Security. The role provides executive market visibility, defines performance metrics, supports organizational change, and builds a high-performing team serving sales, finance, and customer-facing stakeholders.

Own the strategy, roadmap, and investment priorities for foundational agricultural data products, including pipelines, data models, APIs, and shared services. Partner with engineering, architecture, data science, and product teams to deliver scalable, governed, high-quality data capabilities. Prioritize initiatives based on customer and commercial value, define success metrics, resolve cross-team tradeoffs, and expand data support for analytics, predictive modeling, machine learning, and AI applications.

Lead end-to-end LLM inference performance across serving systems, models, GPU hardware, and workloads. Define rigorous benchmarks, diagnose bottlenecks from scheduling through kernels and interconnects, optimize single- and multi-node deployments, and deliver production-ready runtimes and configurations. Collaborate with product and infrastructure teams, evaluate inference technologies, and implement runtime fixes. The role requires strong Python engineering, production experience with serving engines such as vLLM or SGLang, GPU profiling, and knowledge of modern inference optimization techniques.

Build and deploy production machine learning systems that optimize Samsara’s global hardware supply chain. Responsibilities include demand, inventory, lead-time, spend, and supplier-risk forecasting; anomaly detection; feature engineering and ETL; real-time inference; MLOps; data infrastructure improvements; governance; and model monitoring. The role defines the AI transformation roadmap, partners with executive and cross-functional stakeholders, mentors scientists, and drives adoption of AI-enabled operational workflows.

Lead UX design initiatives across a healthcare product suite, solving complex user and business problems through research, prototyping, interaction and visual design. Mentor designers, influence cross-functional teams, contribute to the design system, and establish scalable design standards. Collaborate with engineering, product, leadership, and data science teams to integrate ML features and deliver intuitive, consumer-quality healthcare experiences.

Lead UX design initiatives across a healthcare product suite, solving complex problems through prototyping, user research, and strategic design. Collaborate with engineering, product, leadership, and data science teams to create consumer-quality experiences, integrate ML features, and evolve scalable design systems. Mentor designers, resolve stakeholder feedback, establish design standards, and drive innovation across large-scale projects.

Leads Yahoo’s centralized CRM organization and owns the performance, strategy, governance, operations, innovation, and roadmap for email, push, SMS, newsletters, and other messaging channels. Oversees engagement, retention, revenue, deliverability, personalization, experimentation, quality, compliance, budgets, vendors, and cross-functional partnerships with Product, Engineering, Analytics, Legal, and Marketing. Develops senior leaders and scales AI-enabled CRM capabilities across Yahoo’s global consumer products.

Design, build, evaluate, and productionize machine learning and LLM-based agentic systems for healthcare products. Own projects end-to-end, including problem framing, dataset development, modeling, evaluation, deployment, monitoring, and safety guardrails. Build ML infrastructure, data pipelines, inference systems, and evaluation frameworks. Collaborate with clinicians, product managers, and engineers, while setting technical direction and mentoring team members.

Designs and implements enterprise cloud and AI solutions for unstructured data workloads. Responsibilities include building ingestion pipelines, API integrations, document extraction and HITL workflows, tuning machine learning models, benchmarking performance, and ensuring security, availability, disaster recovery, and data isolation. The role also supports customer developers, leads technical proofs of concept, mentors engineering teams, develops reusable blueprints, and provides feedback to product engineering.

Own and improve Headway’s privacy program across HIPAA, 42 CFR Part 2, state privacy laws, individual rights, incidents, vendor governance, and AI use. Maintain controls, data maps, metrics, training, and operational workflows. Conduct product, vendor, and AI privacy assessments; manage rights requests and incident investigations; coordinate notifications and regulatory submissions; and translate complex requirements into practical guidance for cross-functional teams.

Lead Risk Operations transformation programs from problem definition through implementation and measurement. Own automation initiatives, process redesign, tooling improvements, partner transitions, operational metrics, readiness, and continuous improvement. Collaborate with Risk Operations, Fraud Strategy, Compliance, Product, Engineering, Data, Shared Services, and Vendor Management to deliver measurable gains in service levels, quality, risk outcomes, backlog, and cost.

Conduct research on frontier AI systems, including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarking, and evaluation. Design rigorous experiments, datasets, prototypes, tooling, and research workflows; train and assess models; analyze results; and translate findings into scalable AI products. Collaborate across research, engineering, product, and operations teams, communicate technical conclusions, contribute to publications or open-source work, and mentor engineers and researchers.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Leads Imprint’s fraud prevention strategy across new account, first-party, and transaction fraud. Owns fraud loss outcomes, controls, team performance, and strategic priorities. Manages three fraud leads, partners with modeling and engineering teams, communicates risk and performance to executives, and serves as an operational backstop during severe fraud incidents. Requires deep money-movement fraud expertise, technical fluency in SQL, SAS, or Python, and experience leading fraud teams with loss or P&L accountability.

Build and scale accounting software synchronization solutions connecting BILL’s payment network with third-party accounting platforms. Lead end-to-end software design and delivery, develop scalable AWS microservices, improve platform performance, guide testing and CI/CD practices, resolve customer problems, mentor engineers, and use generative AI to accelerate development.

Drives underwriting innovation by designing, testing, and implementing new tools, technologies, strategies, and processes. Coordinates projects, manages deadlines and risks, supports user acceptance testing, and collaborates with IT, underwriting, data, product, operations, reinsurance, and vendors. Uses data analytics and machine learning to improve risk assessment, efficiency, and customer experience while ensuring regulatory compliance. Provides training and helps translate innovation concepts into adopted underwriting capabilities.

Lead development and productionization of telematics pricing and underwriting models. Responsibilities span statistical modeling, feature engineering, dataset and pipeline development, model deployment, monitoring, data quality validation, troubleshooting, regulatory support, and collaboration with pricing, actuarial, product, engineering, and compliance teams.

Own product positioning, messaging, segmentation, go-to-market strategy, competitive intelligence, customer proof, sales enablement, and thought leadership for Toloka’s enterprise AI data solutions and self-service platform. Translate complex AI and machine learning capabilities into differentiated customer value while partnering with product, sales, marketing, and customers.

Develop autonomy evaluation metrics, statistical and machine-learning analyses, dashboards, and pipelines for simulation and on-road autonomous vehicle testing. Analyze perception, prediction, and planning performance; identify anomalous behavior and critical scenarios; apply VLMs and LLMs where appropriate; and support release gating and safety decisions. The role requires production Python, C++ debugging, technical leadership, cross-functional collaboration, and rigorous software engineering practices.

Define architecture and metrics for autonomous driving evaluation, lead cross-functional integration across autonomy and simulation teams, develop statistical and machine learning methods, analyze large-scale time-series data, manage evaluation KPIs and release gates, and communicate safety and readiness insights through dashboards and stakeholder presentations.

Serves as the technical bridge between customers, Sales, and technology teams. Leads technical discovery, solution architecture, demonstrations, workshops, proofs of concept, and evaluations using HERE data, APIs, mapping, routing, spatial analytics, cloud, AI, and enterprise integration. Partners with Sales to qualify opportunities, reduce technical risk, develop proposals and reusable presales assets, and guide customers toward location-intelligence solutions.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Lead the strategy, roadmap, and execution of an AI-driven B2B SaaS platform for government contracting. Translate RFP and customer needs into prioritized product enhancements, collaborate with AI research and cross-functional teams, apply agile methodologies using Jira, and drive successful product launches and adoption.

Executes systems engineering across R&D platforms, hybrid cloud, SaaS, HPC, containers, integrations, data pipelines, observability, and AI architectures. Coordinates Enterprise IT, vendors, cybersecurity, compliance, and scientific stakeholders to deliver secure, scalable, validated, and supportable solutions. Develops technical documentation, deployment plans, runbooks, monitoring, lifecycle artifacts, risk logs, and operational handoffs. Implements RAG, vector database, AI gateway, agentic workflow, and multimodal integration patterns while supporting cloud migration, change management, governance, and technical issue resolution.