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Jr Machine Learning Engineer Jobs in Wisconsin (NOW HIRING)

WI · On-site

Machine Learning Engineer 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 ...

New

WI · On-site

Als Machine Learning Engineer bouw jij de modellen die energie echt slimmer maken. Je krijgt toegang tot een schat aan real-time data en de vrijheid om modellen van experiment tot productie te ...

WI · On-site

Software Machine Learning Engineer Meet the team Cisco Norway is a global leader in developing video conferencing technology - helping millions of people connect and collaborate worldwide. At our ...

WI · On-site

You are the engineer who prefers the hum of factory equipment to the silence of a cloud notebook, eager to bridge the gap between experimental models and rugged hardware. In this on-site Texas role ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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Jr Machine Learning Engineer information

What does a Jr Machine Learning Engineer do?

A Jr Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the guidance of more senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, model training, testing, and helping to integrate models into production systems. They also work on debugging issues, documenting code, and staying up-to-date with the latest industry trends and tools. Junior engineers typically collaborate closely with cross-functional teams to deliver AI-powered solutions.

What are the key skills and qualifications needed to thrive as a Jr Machine Learning Engineer?

To thrive as a Jr Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, as well as experience with data preprocessing and version control systems, is typically required. Strong analytical thinking, problem-solving skills, and the ability to collaborate effectively help you stand out in this role. These competencies are crucial for developing, optimizing, and deploying machine learning models that address real-world business challenges.

What are some common challenges faced by Jr Machine Learning Engineers in their first year on the job?

Jr Machine Learning Engineers often encounter challenges such as understanding complex codebases, managing large datasets, and bridging the gap between academic concepts and real-world applications. Collaboration with data scientists, software engineers, and product teams can also be a learning curve, as effective communication is crucial for project success. Additionally, balancing tasks like model development, testing, and deployment within fast-paced agile environments can be demanding, but these experiences provide valuable opportunities for skill growth and professional development.

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

AspectJr Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often with advanced certifications
Work EnvironmentFocus on developing and deploying ML models, coding, and data preprocessingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, consulting, research institutions

The Jr Machine Learning Engineer primarily develops and deploys ML models, requiring coding skills and familiarity with ML frameworks. Data Scientists analyze data, build statistical models, and interpret insights. While both roles work with data, the Jr Machine Learning Engineer is more focused on implementation, whereas Data Scientists focus on analysis and strategy.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, industry, and experience. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
Infographic showing various Jr 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 29 days ago


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.