ML Engineer Visa Sponsorship Jobs in Wisconsin
Wisconsin's ML engineer hiring is anchored by companies like American Family Insurance, Epic Systems, and Exact Sciences, with Madison and Milwaukee as the primary tech hubs. Employers in insurance, health tech, and biotech regularly sponsor H-1B visas for machine learning roles, making Wisconsin a realistic target for international ML engineers seeking sponsorship.
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Get Access To All JobsAbout the Role
In this role, you will focus on MLOps, supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure, tools, and best practices across the Machine Learning Engineering (MLE) ecosystem.
What You’ll Do
- Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient model development through cloud infrastructure and tooling
- Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance, scalability, and cost efficiency
- Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation
- Partner with and support Data Scientists by enabling effective use of cloud-based tools and infrastructure, and providing technical expertise across the ML lifecycle
- Collaborate with machine learning engineers to share knowledge, improve best practices, and foster a culture of continuous learning and development
- Support development and maintain monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure
- Develop, document, and communicate implementations and best practices across the data science lifecycle
- Manage and communicate cloud infrastructure costs and budgets to project stakeholders
- Stay current with GCP services and evolving best practices in Machine Learning Engineering and MLOps
- Additional tasks may be assigned
What Skills You Have
Required
- Experience in MLOps or DevOps practices, including building and operating production ML systems using Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving (batch and real-time), and automated testing frameworks
- Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field
- Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments
- 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery
- In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc
- Extensive expertise with CI/CD and IaC best practices
- Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL
- Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience working in Agile environments with an emphasis on iterative development and continuous delivery
Preferred
- Master’s Degree
- Proficiency in Java or other languages
- Retail experience
- E-commerce experience
- 5+ years of experience in Machine Learning
- Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming)
- Experience working with agent based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents
About the Role
In this role, you will focus on MLOps, supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure, tools, and best practices across the Machine Learning Engineering (MLE) ecosystem.
What You’ll Do
- Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient model development through cloud infrastructure and tooling
- Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance, scalability, and cost efficiency
- Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation
- Partner with and support Data Scientists by enabling effective use of cloud-based tools and infrastructure, and providing technical expertise across the ML lifecycle
- Collaborate with machine learning engineers to share knowledge, improve best practices, and foster a culture of continuous learning and development
- Support development and maintain monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure
- Develop, document, and communicate implementations and best practices across the data science lifecycle
- Manage and communicate cloud infrastructure costs and budgets to project stakeholders
- Stay current with GCP services and evolving best practices in Machine Learning Engineering and MLOps
- Additional tasks may be assigned
What Skills You Have
Required
- Experience in MLOps or DevOps practices, including building and operating production ML systems using Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving (batch and real-time), and automated testing frameworks
- Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field
- Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments
- 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery
- In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc
- Extensive expertise with CI/CD and IaC best practices
- Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL
- Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience working in Agile environments with an emphasis on iterative development and continuous delivery
Preferred
- Master’s Degree
- Proficiency in Java or other languages
- Retail experience
- E-commerce experience
- 5+ years of experience in Machine Learning
- Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming)
- Experience working with agent based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents
ML Engineer Job Roles in Wisconsin
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Search ML Engineer Jobs in WisconsinML Engineer Jobs in Wisconsin: Frequently Asked Questions
Which companies sponsor visas for ML engineers in Wisconsin?
American Family Insurance and Epic Systems in Madison are among the more consistent H-1B sponsors for technical roles, including machine learning positions. Exact Sciences and Advocate Aurora Health also file for ML and data science talent. Wisconsin's insurance and health tech sectors drive most of the sponsorship activity, alongside a smaller number of manufacturing and agriculture technology firms based in the state.
Which visa types are most common for ML engineer roles in Wisconsin?
The H-1B is the most common visa for ML engineers in Wisconsin. It requires a bachelor's degree or higher in a relevant field such as computer science, statistics, or engineering, and the employer must file a Labor Condition Application with the Department of Labor. Candidates already holding OPT or STEM OPT authorization can often begin work before H-1B approval, which many Wisconsin employers accommodate.
How to find ml engineer visa sponsorship jobs in Wisconsin?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search ML engineer roles in Wisconsin without sifting through positions that won't support international candidates. Given that sponsorship-willing employers in Wisconsin are concentrated in Madison and Milwaukee across health tech, insurance, and biotech, filtering by those industries on Migrate Mate helps narrow the search efficiently.
Which cities in Wisconsin have the most ML engineer sponsorship jobs?
Madison is Wisconsin's primary hub for ML engineering sponsorship, driven by Epic Systems, American Family Insurance, and the University of Wisconsin-Madison's research and commercialization activity. Milwaukee follows, with activity from health systems and financial services firms. Smaller but notable pockets exist in the Fox Valley corridor where manufacturing automation companies have increased their demand for machine learning talent.
Are there state-specific considerations for ML engineers pursuing sponsorship in Wisconsin?
Wisconsin's ML hiring leans heavily on health informatics, insurance analytics, and agricultural technology rather than pure software, so candidates whose experience intersects with those domains tend to be more competitive locally. The University of Wisconsin-Madison produces a steady pipeline of ML graduates, which means employer familiarity with OPT and H-1B processes is relatively high among mid-to-large Wisconsin tech employers compared to less university-proximate states.
What is the prevailing wage for sponsored ml engineer jobs in Wisconsin?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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