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Internship Machine Learning Engineer Jobs in Wisconsin

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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Internship Machine Learning Engineer information

What does an internship machine learning engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

What types of projects and responsibilities can I expect as an internship machine learning engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

What is the difference between Internship Machine Learning Engineer vs Data Scientist Intern?

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What are the most commonly searched types of Machine Learning Engineer jobs in Wisconsin?

The most popular types of Machine Learning Engineer jobs in Wisconsin are:

What cities in Wisconsin are hiring for Internship Machine Learning Engineer jobs?

Cities in Wisconsin with the most Internship Machine Learning Engineer job openings:

Infographic showing various Internship Machine Learning Engineer job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer II

Brookfield, WI • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 24 days ago


Key responsibilities

  • Create, develop, and validate machine learning models.

  • Work with cross-functional teams to integrate machine learning solutions into Milwaukee products.

  • Innovate and explore new machine learning methods for deployment in power tool solutions.


Job description

Machine Learning Engineer

Job Description:

Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.

At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions on our engineering teams. Our Engineering Team is responsible for giving life to the batteries, motors, and electronics that power solutions changing the lives of our users. Every developmental phase of these critical components happens in-house under the watch of this team. We continue to invest in engineering resources to design and develop leadership in electronic capabilities; something unique within the industry. And we're pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence.

Your role on our team

As a Machine Learning Engineer II, you will create, develop, and validate machine learning models while working with highly cross-functional teams to make power tool solutions that change the lives of our users. You will innovate and explore new machine learning solutions to deploy into Milwaukee products around the world while demonstrating excellent problem-solving skills, critical thinking, and the ability to thrive under pressure in a dynamic environment. Success in this role also requires strong technical communication skills and fundamental project management abilities, along with a proactive sense of ownership for projects and tasks and an understanding of how they connect to broader initiatives.

What TOOLS you'll bring with you:

  • Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.

  • Completed course work or specialization in Machine Learning and/or Data Science

  • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field

  • Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)

  • Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision

  • Proficient developing and debugging code in Python

  • Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)

  • Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)

  • Sold mathematical foundation in statistics, linear algebra, calculus and optimization

  • Experience working with modern software development tools and version control tools

  • Excellent problem-solving skills, critical thinking, and ability to work well under pressure in a dynamic environment.

  • Excellent technical communication skills and fundamental project management abilities

  • Demonstrated strong sense of ownership of a project or tasks and understanding of relationships to other tasks/projects

  • Ability to travel up to 10% of the time (domestic and international).

Other TOOLS we prefer you to have:

  • Master's degree or PhD in Machine Learning or related field is preferred

  • At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field (an advanced degree may count toward some experience)

  • Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing

  • Proven track record of developing, deploying and implementing AI or ML solutions connected to business objectives

  • Proficient developing and debugging code in an embedded environment in a programming language such as C or C++

  • Working knowledge of various sensor technologies (e.g. IMU, thermistors, magnetic and optical) and interfacing to microcontrollers

  • Working knowledge of embedded systems architecture (HW & SW), microcontroller design and operation

  • Experience with different types of data collection methods, understanding their principles and demonstrating their value in relevant environments

  • Experience developing and deploying machine learning algorithms to edge environments

  • Demonstrated ability to develop robust MLOps pipelines and ensure efficient deployment, monitoring and scaling of ML models

We provide these great perks and benefits:

  • Robust health, dental and vision insurance plans.

  • Generous 401 (K) savings plan.

  • Education assistance.

  • On-site wellness, fitness center, food, and coffee service.

  • And many more, check out our benefits site HERE.

Milwaukee Tool is an equal opportunity employer.