Machine Learning Jobs in Wisconsin
Machine Learning jobs in Wisconsin are concentrated in Madison, Milwaukee, and the Fox Valley corridor, where employers like American Family Insurance, Epic Systems, and Northwestern Mutual maintain active data science and AI teams. Demand is strongest in model development, natural language processing, and computer vision, with roles ranging from junior ML engineer to senior research scientist. Wisconsin's insurance, healthcare IT, and financial services sectors are among the most consistent sources of machine learning hiring in the Midwest. See the openings below and apply to the ones that match your experience.
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Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you’re ready to pursue your fullest potential, we want to get to know you!
Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first).
Job Summary:
We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact.
The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences.
Job Specifications:
Starting Wage: $140,000 - $185,000 + Annual Bonus
Employment Type: Year Round
Shift Type: Full Time hours available
Minimum Age: At least 18 years of age
Housing Availability: No
Job Responsibilities:
- Productionize ML models developed by data science into reliable, monitored, maintainable systems.
- Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable.
- Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows.
- Identify and scope opportunities for ML engineering across the business for high-impact.
- Develop reusable tools, libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams.
- Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users.
- Prepare the platform for future AI engineering, including LLM and agent-based systems, as the organization matures.
- Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews.
Job Requirements:
Technical Skills:
- Quantitative Foundation: B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering).
- Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts.
- Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services.
- Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
- ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement.
- Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback.
- Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture.
- Databricks Expertise: You’re familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance.
- DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability.
- Application Development: You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs.
- System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use.
Soft Skills:
- Curious: bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning.
- Ownership: take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions.
- Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences.
- Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders.
- Pragmatism: You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship.
Preferred qualifications:
- A graduate degree (Masters or PhD) in a quantitative field
- Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
- Experience with AI engineer to use, build, and monitor agentic solutions
The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors.
Job Benefits
- Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons
- MORE employee discounts on lodging, food, gear, and mountain shuttles
- 401(k) Retirement Plan
- Employee Assistance Program
- Excellent training and professional development
Full Time roles are eligible for the above, plus:
- Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours)
- Free ski passes for dependents
- Critical Illness and Accident plans
Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states* in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming.
Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion.
In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution.
We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers.
Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law.
Requisition ID 517322
Reference Date: 09/05/2026
Job Code Function: Data Science
Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you’re ready to pursue your fullest potential, we want to get to know you!
Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first).
Job Summary:
We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact.
The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences.
Job Specifications:
Starting Wage: $140,000 - $185,000 + Annual Bonus
Employment Type: Year Round
Shift Type: Full Time hours available
Minimum Age: At least 18 years of age
Housing Availability: No
Job Responsibilities:
- Productionize ML models developed by data science into reliable, monitored, maintainable systems.
- Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable.
- Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows.
- Identify and scope opportunities for ML engineering across the business for high-impact.
- Develop reusable tools, libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams.
- Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users.
- Prepare the platform for future AI engineering, including LLM and agent-based systems, as the organization matures.
- Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews.
Job Requirements:
Technical Skills:
- Quantitative Foundation: B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering).
- Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts.
- Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services.
- Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
- ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement.
- Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback.
- Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture.
- Databricks Expertise: You’re familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance.
- DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability.
- Application Development: You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs.
- System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use.
Soft Skills:
- Curious: bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning.
- Ownership: take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions.
- Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences.
- Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders.
- Pragmatism: You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship.
Preferred qualifications:
- A graduate degree (Masters or PhD) in a quantitative field
- Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
- Experience with AI engineer to use, build, and monitor agentic solutions
The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors.
Job Benefits
- Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons
- MORE employee discounts on lodging, food, gear, and mountain shuttles
- 401(k) Retirement Plan
- Employee Assistance Program
- Excellent training and professional development
Full Time roles are eligible for the above, plus:
- Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours)
- Free ski passes for dependents
- Critical Illness and Accident plans
Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states* in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming.
Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion.
In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution.
We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers.
Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law.
Requisition ID 517322
Reference Date: 09/05/2026
Job Code Function: Data Science
See All 6 Machine Learning Jobs in Wisconsin
Find roles in Wisconsin that match your experience and apply in just a few clicks.
Find Machine Learning JobsMachine Learning Jobs by City in Wisconsin
Where Wisconsin roles are concentrated, by current openings.
Machine Learning Job Market in Wisconsin
A snapshot from current Wisconsin openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
What Wisconsin Employers Look For
The qualifications that appear most often in machine learning jobs across Wisconsin.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience building, training, and deploying supervised and unsupervised models in production environments
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for ML pipeline deployment
- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques
- Ability to communicate model results and technical findings clearly to non-technical stakeholders
Machine Learning Jobs in Wisconsin: Frequently Asked Questions
How do you become a machine learning engineer in Wisconsin?
Machine learning roles in Wisconsin do not require a state-issued license. Most employers hire candidates who hold a bachelor's or master's degree in computer science, mathematics, statistics, or a closely related field. Building a portfolio of projects on platforms like GitHub, completing recognized ML certifications, and gaining hands-on experience through internships at Wisconsin research universities or industry labs strengthens your candidacy considerably.
Which companies hire machine learning engineers in Wisconsin?
Wisconsin machine learning roles are posted by Paradigm, CVS Health, and Vail Resorts and others right now, based on current listings on Migrate Mate as of September 2026. Wisconsin's concentration of insurance carriers, healthcare IT firms, and financial services companies means demand is particularly consistent outside of pure tech sectors.
Which Wisconsin cities have the most machine learning jobs?
Brookfield, Wisconsin, and Madison lead Wisconsin for machine learning openings. Madison anchors the market through its university research ecosystem and corporate headquarters including Epic Systems and American Family Insurance, while Milwaukee draws hiring from financial services and healthcare technology firms, and smaller markets reflect satellite offices of those same large employers.
Are there remote machine learning jobs in Wisconsin?
Yes, and more than most fields. About 0% of machine learning openings tied to Wisconsin are remote or hybrid as of September 2026, reflecting how well the work translates to distributed teams. Model development, experimentation, and research roles are the most likely to be fully remote, while roles requiring close collaboration with on-site data infrastructure tend to be hybrid.
How can I get hired as a machine learning engineer in Wisconsin with little or no experience?
The most realistic entry path is through a data analyst or software engineer role at a large Wisconsin employer, then transitioning internally once you demonstrate ML skills. Epic Systems, American Family Insurance, and Northwestern Mutual run structured associate and rotational programs where candidates with strong fundamentals move into applied ML work. Building a public portfolio of end-to-end projects, contributing to open-source repositories, and completing a recognized ML certification gives Wisconsin hiring managers a concrete signal when your professional experience is limited.
Where can I find and apply to machine learning jobs in Wisconsin?
You can find and apply to machine learning jobs in Wisconsin on Migrate Mate, which lists current openings from employers across the state. Search the listings to find roles that match your background, skills, and preferred location, then apply directly to the ones that fit.
See All 6 Machine Learning Jobs in Wisconsin
Find roles in Wisconsin that match your experience and apply in just a few clicks.
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