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Research Machine Learning Federated Learning Jobs in Wisconsin

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 ...

$107K - $139K/yr

United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning developers and ...

$118K - $153K/yr

United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning developers and ...

$225K - $260K/yr

The role collaborates closely with ML researchers and infrastructure teams, influencing the design ... Hands-on experience training machine learning models across multiple GPUs or compute nodes ...

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Machine Learning Tutor

Madison, WI · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

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Research Machine Learning Federated Learning information

What are the key skills and qualifications needed to thrive as a Researcher in Machine Learning Federated Learning, and why are they important?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is a Researcher in Machine Learning Federated Learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Research Machine Learning Federated Learning jobs in Wisconsin? For Research Machine Learning Federated Learning jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Research Machine Learning Federated Learning jobs in Wisconsin look for? The top searched job categories for Research Machine Learning Federated Learning jobs in Wisconsin are:
Infographic showing various Research Machine Learning Federated Learning job openings in Wisconsin as of July 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution.

Full-time

Retirement

Posted 24 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!