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Scientific Machine Learning Jobs in Wisconsin (NOW HIRING)

Yaskawa

Machine Learning Engineer

Franklin, WI · On-site

The ideal candidate will possess a Bachelor's degree in Computer Science, Computer Engineering ... If the Machine Learning Engineer role sounds like a fit for your background and career goals, we ...

Varsity Tutors

Machine Learning Tutor

Madison, WI · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Serve Robotics

$225K - $260K/yr

Work closely with ML scientists and other engineers to integrate new models, experiments, and ... Hands-on experience training machine learning models across multiple GPUs or compute nodes ...

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Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Wisconsin? For Scientific Machine Learning jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Wisconsin look for? The top searched job categories for Scientific Machine Learning jobs in Wisconsin are:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Wisconsin as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 2% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Yaskawa Electric America

Franklin, WI

Full-time

Retirement

Posted 21 days ago

Job description

Yaskawa America, Inc. - Drives & Motion Division is a U.S. corporation, created to provide Automation Solutions and Support to our customers in North America, Central America, and South America. Yaskawa is the world's largest manufacturer of AC Inverter Drives, Servo and Motion Control, and Robotics Automation Systems. Products are marketed through direct sales, partners, representatives, dealers, and distributors. Yaskawa America, Inc. - Drives & Motion Division is a wholly-owned corporation of Yaskawa Electric Corporation of Japan. Since 1915, Yaskawa Electric has served the world needs for products to improve global productivity through Automation. We look to hire people who value a positive work culture, want to be part of a winning team, and have a desire to learn and grow. Yaskawa's culture of continuous improvement values hiring individuals that are looking for the opportunity to stretch their current talents and skills to the next level and beyond.  If you have a passion for machine learning and advanced technology, we may have the perfect opportunity for you!

In this role you will support the identification and implementation of machine learning solutions across the Operations Business Unit. This engineer will work with the guidance of Operations team members to develop models, maintain automated systems, and contribute to simulation and digital twin projects that improve operational efficiency , quality and throughput. 

The ideal candidate will possess a Bachelor's degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, Industrial Engineering or a related field.  To be successful you should have 0-3 years of of professional or internship experience in machine learning, data science, or software engineering. Also proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Understanding of fundamental ML concepts: regression, classification, clustering, and model evaluation is a must. 

Some key advantages of working at Yaskawa include: career opportunities in diverse areas, a highly competitive benefit package, including a generous 401(K) plan, profit sharing, corporate wide bonus plan and educational assistance program offering up to $10,000 a year for graduate courses. Additional information regarding the benefit package can be found at the following link. 

https://www.yaskawa.com/about-us/careers/benefits

If the Machine Learning Engineer role sounds like a fit for your background and career goals, we would love to hear from you!

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