Machine Learning Intern Jobs in Minnesota
Machine Learning Intern jobs in Minnesota concentrate in medical technology, financial services, and enterprise software, with the Twin Cities metro anchoring most of the state's activity alongside growing demand in Rochester and Duluth. Organizations like UnitedHealth Group, 3M, and Cargill have established machine learning programs that regularly bring in interns across computer vision, natural language processing, and predictive analytics. Minnesota ranks among the more active Midwest markets for this role, drawing candidates from the University of Minnesota, Minnesota State, and the region's strong STEM pipeline. Find a role that fits below and apply directly.
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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 7 Machine Learning Intern Jobs in Minnesota
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Find Machine Learning Intern JobsMachine Learning Intern Jobs by City in Minnesota
Where Minnesota roles are concentrated, by current openings.
Machine Learning Intern Job Market in Minnesota
A snapshot from current Minnesota openings, updated as new roles post.
Who's Hiring
What Minnesota Employers Look For
The qualifications that appear most often in machine learning intern jobs across Minnesota.
- Enrollment in a bachelor's or master's program in computer science, statistics, or a related field
- Hands-on experience with Python and core machine learning libraries such as TensorFlow or PyTorch
- Familiarity with supervised and unsupervised learning methods and model evaluation techniques
- Experience working with structured and unstructured datasets and tools such as SQL or Spark
- Strong foundation in linear algebra, probability, and statistical inference from coursework
- Ability to communicate model findings clearly to technical and non-technical stakeholders
Machine Learning Intern Jobs in Minnesota: Frequently Asked Questions
How do you become a machine learning intern in Minnesota?
Machine learning intern roles in Minnesota do not require a state-issued license or certification. The typical path is enrollment in a computer science, data science, or statistics program at a Minnesota institution such as the University of Minnesota Twin Cities or Minnesota State University, combined with hands-on project work demonstrating model-building skills. Employers look for coursework in algorithms, probability, and data engineering, plus a portfolio or GitHub repository showing applied work in Python or R.
Which companies hire machine learning interns in Minnesota?
Companies currently hiring machine learning interns in Minnesota include Loram, Target, and Kitware, per current listings on Migrate Mate as of September 2026. Minnesota's concentration of large medtech, insurance, and agribusiness headquarters means internship programs here often focus on applied ML in healthcare data, risk modeling, and supply chain optimization.
Which Minnesota cities have the most machine learning intern jobs?
Minneapolis, Minnesota, and Hamel have the most machine learning intern openings in Minnesota. The Minneapolis-Saint Paul metro drives the majority of demand, anchored by the headquarters of major insurance carriers, financial firms, and medtech companies, while Rochester's presence of large healthcare and technology employers contributes to openings outside the Twin Cities.
Are there remote machine learning intern jobs in Minnesota?
Yes, and more than most fields, since machine learning intern work is primarily analytical and code-based. About 50% of machine learning intern openings tied to Minnesota are remote or hybrid as of September 2026, reflecting the desk-based nature of the role. Model development, data preprocessing, and research tasks transfer well to remote settings, though production deployment work often requires some on-site collaboration.
How can I get hired as a machine learning intern in Minnesota with little or no experience?
The most realistic entry path is applying to structured internship programs at large Minnesota employers such as UnitedHealth Group, 3M, or Mayo Clinic, which run formal summer cohorts designed for students early in their programs. Building a public portfolio of ML projects on GitHub, contributing to open-source tools, or completing a Kaggle competition gives hiring managers something concrete to evaluate. Adjacent roles like data analyst intern or software engineering intern at Minnesota-based companies also provide a strong stepping stone into a dedicated machine learning track.
Where can I find and apply to machine learning intern jobs in Minnesota?
You can find and apply to machine learning intern jobs in Minnesota on Migrate Mate, which lists current openings across the state. Find roles that fit your background and apply directly to the employers posting them.
See All 7 Machine Learning Intern Jobs in Minnesota
Find roles in Minnesota that match your experience and apply in just a few clicks.
Find Machine Learning Intern Jobs