Top Machine Learning Jobs in Milwaukee, WI

Leads technical pre-sales for supply chain integration solutions, partnering with Sales to conduct discovery, design ERP/WMS/TMS and trading-partner architectures, run POCs, deliver demonstrations, and respond to RFPs. Advises technical and executive stakeholders on business outcomes and AI opportunities, translates capabilities into measurable ROI, and collaborates with Product, Customer Success, and Professional Services on roadmap feedback and post-sale handoffs.

Owns revenue and pipeline accountability for an enterprise marketing analytics software portfolio and assigned geography. Leads complex software sales cycles, negotiates commercial terms, engages executive buyers, develops partner channels, coordinates sales professionals, and manages forecasts. The role requires deep expertise in marketing measurement, attribution, optimization, analytics, SaaS and AI-native software, along with the ability to translate technical capabilities into measurable business outcomes for senior marketing, finance, commerce, data, and technology stakeholders.

Leads enterprise software pre-sales activities, including discovery, product demonstrations, RFP responses, solution scoping, workshops, proof-of-concepts, and proposal development. Supports partners and industry events, creates reusable sales enablement assets, and collaborates with sales, product, legal, delivery, analytics, and technology teams. Advises senior clients on marketing measurement, attribution, forecasting, optimization, AI-native software, and investment effectiveness while advancing complex sales opportunities.

Leads enterprise sales for procurement software across an assigned product cluster and geography. Owns revenue targets, pipeline development, complex C-suite sales cycles, pricing, negotiations, renewals, forecasting, and partner-channel growth. Coordinates a small sales team, collaborates with account and presales teams, attends industry events, and positions AI-native procurement solutions using ROI and value-based narratives. Requires extensive enterprise software sales experience, seven-figure deal success, procurement technology expertise, and experience selling AI-native products.

Leads enterprise software pre-sales for an AI-native supply chain platform. Responsibilities include discovery, product demonstrations, RFP and proposal responses, client workshops, proof-of-concept scoping, deployment architecture design, partner enablement, event support, and reusable sales asset development. The role requires deep expertise in supply chain planning, AI-native architecture, SAP IBP integration, enterprise software delivery, and technical presentations to executive and technical stakeholders.

Owns end-to-end enterprise software sales revenue for Accenture’s Media Suite across an assigned product cluster and geography. Leads complex, multi-year sales cycles, builds pipeline, engages C-suite buyers, negotiates commercial terms, and develops value-based proposals. Coordinates internal sales teams, pre-sales resources, and technology partners, including Microsoft and AWS. Manages partner co-selling, forecasts, CRM reporting, industry events, and go-to-market initiatives while targeting media and entertainment organizations.

Originates and qualifies enterprise software sales opportunities for supply chain solutions, manages pipeline and forecasts, conducts discovery, develops value propositions and commercial proposals, coordinates presales resources, supports negotiations, and advances deals through close. Engages senior supply chain and executive buyers across industries, supports channel partners and junior sellers, attends industry events, and provides competitive intelligence. The role requires enterprise software sales expertise, AI-native product knowledge, supply chain understanding, and hyperscaler co-sell experience.

Originates and advances enterprise software sales opportunities for manufacturing clients. Responsibilities include pipeline development, discovery, value proposition and business case creation, proposal delivery, deal coordination, partner support, forecasting, CRM management, and contract negotiation. The role requires selling AI-native SaaS and platform solutions, understanding manufacturing technologies and OT/IT convergence, engaging executive and operational buyers, building land-and-expand motions, and translating operational outcomes into financial value.

Lead pre-sales for AI-enabled manufacturing software, including discovery, solution demonstrations, RFP responses, workshops, proof-of-concepts, and proposal development. Partner with sales teams, technology partners, and clients to design solutions integrating manufacturing systems, OT/IT data, ERP, cloud, and agentic AI platforms. Create reusable sales assets, support industry events, enable team members, and contribute to pipeline reporting and win/loss reviews. The role requires extensive enterprise software pre-sales experience and frequent client travel.

Lead product strategy, roadmap, and delivery for Falcon Complete’s internal MDR tooling, including AI-powered investigation and triage, ticketing, case management, and analyst workbench systems. Partner with security operations, analysts, engineering, and data science teams to translate workflows into product requirements, prioritize automation, improve analyst productivity and response times, define success metrics, and enhance customer outcomes.

Own the strategy, architecture, development, deployment, monitoring, and continuous improvement of production personalization and recommendation systems. Build custom embeddings, ranking models, and shared representations across feeds, search, and recommendations. Lead ambiguous problems from concept to measurable customer impact, establish AI evaluation standards, partner with product and data teams, make cross-team technical decisions, and coach senior engineers.

Participate in a four-rotation information technology program with six-month project assignments across technology development and analytics. Potential rotations include cybersecurity, data engineering, AI and machine learning, automation, application development, cloud engineering, enterprise architecture, IT strategy, and end-user experience. Associates build technical, analytical, collaboration, and process-improvement skills while contributing to cross-functional technology initiatives.

Leads client-facing generative AI and data modernization engagements, directing solution design, delivery planning, architecture, and technical decisions. Guides teams in prompt engineering, context engineering, agent orchestration, LLM evaluation, RAG, vector databases, and AI guardrails. Oversees cloud AI implementations using Gemini, Vertex AI, AWS Bedrock, or Azure AI Services; develops Python prototypes; evaluates model performance; manages workstreams and deliverables; and mentors staff on AI methods, agile delivery, and technical problem-solving.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Designs, deploys, and secures operational technology systems across manufacturing facilities. The role connects plant equipment with MES, CMMS, ERP, SCADA, historian, and cloud platforms; builds AWS-based OT infrastructure; enables machine monitoring and predictive maintenance; and supports cybersecurity, network segmentation, vulnerability management, incident response, and disaster recovery. Works cross-functionally with Operations, Maintenance, Engineering, IT, Cybersecurity, Quality, and Supply Chain teams to advance connected-factory capabilities.

Develop and optimize CT image quality, calibration, dose management, and system safety features. Collaborate cross-functionally to evaluate complex designs, define performance requirements, investigate technical risks and customer issues, lead design reviews, and drive system-level tradeoffs. The role requires expertise in CT imaging, image and signal processing, and system architecture, while also providing technical leadership, mentoring, and innovation for new medical imaging products.

Leads a global AI, analytics, and data organization supporting integrated supply chain processes. Owns the enterprise digital and AI roadmap, governed KPI products, data governance, self-service analytics, and the Heartbeat single source of truth. Manages leaders and technical teams, arbitrates KPI definitions, partners with senior stakeholders, and scales AI capabilities including predictive analytics, simulation, optimization, digital twins, generative AI, and agentic AI across a hub-and-spoke operating model.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Own and scale Jellyfish’s security engineering program, including strategy, architecture, secure SDLC governance, AI security, threat modeling, vulnerability remediation, incident response, penetration testing, and bug bounty programs. The role combines hands-on software development with executive advising, cross-functional leadership, mentorship, and security risk management across SaaS infrastructure and customer-facing AI products.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Master’s-level intern supporting AI solutions for manufacturing, supply chain, quality, and corporate operations. Responsibilities include analyzing operational data, developing models and dashboards, supporting machine learning and generative AI pilots, researching emerging technologies, collaborating with stakeholders, and presenting recommendations. Projects may involve demand planning, procurement analytics, inventory forecasting, process automation, predictive maintenance, and business intelligence. The role is onsite at Generac’s headquarters in Waukesha, Wisconsin.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Leads multiple engineering teams and platform initiatives, setting roadmaps, improving developer experience, and overseeing software delivery, reliability, security, and scalability. Guides AI and automation adoption, strengthens CI/CD and cloud practices, develops engineering leaders, manages technical debt, and partners with product, business, and security stakeholders to deliver measurable outcomes.