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Applied Engineer Jobs in Wisconsin (NOW HIRING)

Senior Research Engineer

Madison, WI · On-site +1

$105K - $144K/yr

Unlike traditional engineering consulting, this role combines applied engineering, field research, emerging technologies, and strategic problem solving. Our engineers work across research ...

Our Applied AI organization is a fast-moving, dedicated group of Forward Deployed Engineers (FDEs), Industry & Applied AI Specialists, and business strategy leaders committed to establishing Cloudera ...

Our Applied AI organization is a fast-moving, dedicated group of Forward Deployed Engineers (FDEs), Industry & Applied AI Specialists, and business strategy leaders committed to establishing Cloudera ...

Our Applied AI organization is a fast-moving, dedicated group of Forward Deployed Engineers (FDEs), Industry & Applied AI Specialists, and business strategy leaders committed to establishing Cloudera ...

Applied Mathematics Tutor

Madison, WI · Remote

$18 - $40/hr

... engineering, physics, finance, and computational science applications. * Conceptual Teaching ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... engineering, physics, finance, and computational science applications. * Conceptual Teaching ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

Strong applied AI and software engineering fundamentals * Builderswho canspantech,product,and designthinkingwithhigh autonomy * Bias for shipping, iterating, and following customer feedback over ...

Showing results 21-40

Applied Engineer information

See Wisconsin salary details

$10

$47

$88

How much do applied engineer jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for applied engineer in Wisconsin is $47.53, according to ZipRecruiter salary data. Most workers in this role earn between $36.15 and $61.39 per hour, depending on experience, location, and employer.

What is an applied engineer?

Applied engineers are professionals who use principles of engineering, mathematics, and science to solve practical problems and improve processes in various industries. Unlike theoretical engineers, applied engineers focus on implementing and optimizing technology, equipment, and systems in real-world settings. They often work in manufacturing, product development, quality control, and operations, bridging the gap between design and production. Applied engineers are skilled in troubleshooting, project management, and applying technical knowledge to enhance efficiency and innovation.

How do applied engineers typically collaborate with cross-functional teams during project development?

Applied Engineers often play a central role in project development by bridging the gap between design concepts and practical implementation. They work closely with teams from R&D, manufacturing, and quality assurance to ensure that solutions are both innovative and feasible. Regular meetings, collaborative problem-solving sessions, and clear communication are essential to address technical challenges and align project goals. This collaborative environment not only enhances project outcomes but also provides opportunities for Applied Engineers to learn from other disciplines and advance their careers.

What are the key skills and qualifications needed to thrive as an applied engineer?

To thrive as an Applied Engineer, you need a strong background in engineering principles, problem-solving, and project management, typically supported by a degree in engineering or a related field. Familiarity with CAD software, manufacturing systems, and quality control tools, as well as certifications like Six Sigma or Lean, are commonly required. Strong analytical thinking, effective communication, and teamwork skills help distinguish top performers in this role. These abilities ensure efficient project execution, innovative solutions, and successful collaboration within multidisciplinary teams.

What jobs can you get with applied engineering?

Applied engineers can pursue roles such as product development engineer, systems engineer, manufacturing engineer, or research engineer. These positions often require skills in problem-solving, technical knowledge, and proficiency with tools like CAD software or programming languages, and may involve working in industries like aerospace, automotive, or electronics.

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

The most popular types of Applied Engineer jobs in Wisconsin are:

What are popular job titles related to Applied Engineer jobs in Wisconsin?

For Applied Engineer jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Applied Engineer jobs in Wisconsin look for?

The top searched job categories for Applied Engineer jobs in Wisconsin are:

Infographic showing various Applied Engineer job openings in Wisconsin as of August 2026, with employment types broken down into 88% Full Time, 7% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $98,856 per year, or $47.5 per hour.

Applied Machine Learning Engineer I - Advanced Engineering & Technology

Milwaukee Tool

Brookfield, WI

Full-time

Medical, Dental, Vision, Retirement

Re-posted yesterday


Job description

Job Description:

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

INNOVATE WITHOUT BOUNDARIES!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.

Your Role on the Team:

As a member of the Advanced Engineering and Technology (AET) Team in the Power Tool Accessories business unit you will utilize your expertise in machine learning to solve problems where no established solution exists and deliver first-of-its-kind technologies at Milwaukee Tool. You will support the research, prototyping, and delivery of ML-driven capabilities that accelerate how we design and develop products. You will take ideas from conceptual whiteboard architectures through functional prototypes and support hand-off integrations, delivering technology innovation to product and production engineering teams. This role is an individual contributor position focused on applied execution and technology demonstration, working under shared technical direction.

Why This Role is Different:

  • FullStack ML in a Physical Domain: Work across the ML stack, from machine and sensorlevel data through model deployment on edge hardware or cloud infrastructure.
  • R&D Engineering First: Apply ML across Technology Readiness Levels (TRL 1-7), bringing technology innovation to life beyond model tuning. Domain knowledge in materials, mechanics, signals, or physics is central to this role.
  • Flexible Tools: Select and use frameworks and libraries best suited to the problem, without being constrained to a single ecosystem.
  • Real Impact: Deliver MLdriven capabilities that shorten product development cycles and unlock new engineering possibilities at Milwaukee Tool.

What You'll Do:

  • Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
  • Frame engineering problems as ML problems by assessing ML value versus physicsbased or analytical approaches and defining practical success criteria.
  • Design, train, and evaluate ML models to help solve well-scoped applied science and engineering problems, working under the guidance of senior engineers.
  • Build ML workflows spanning data acquisition, feature engineering, model development, and validation using standard scientific and ML libraries (NumPy, Pandas, scikit-learn, PyTorch, TensorFlow).
  • Support algorithm selection and the construction of standard feature sets for engineering problems.
  • Support the deployment of ML models on edge hardware and cloud infrastructure, building and deploying with guidance.
  • Deploy ML enabled systems on edge hardware and cloud infrastructure to support engineering decisions.
  • Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption.
  • Conduct experiments and data analysis following established patterns and methods; identify and debug basic model errors.
  • Organize, clean, and prepare data for downstream tasks, and create visualizations that support hypotheses, insights, and conclusions.
  • Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs, and support the design of data collection and test plans.
  • Research and learn about emerging AI and ML technologies through literature, universities, conferences, and vendor engagement.

What You'll Bring:

  • BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine Learning.
  • Experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
  • Demonstrated experience designing, training, and evaluating ML models on real-world or academic problems.
  • Working knowledge of Python and the scientific computing ecosystem (NumPy, SciPy, Pandas, scikit-learn), with familiarity with SQL.
  • Exposure to at least one deep learning framework (PyTorch or TensorFlow), including training models, and awareness of cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
  • Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
  • Ability to help formulate well-scoped engineering or scientific tasks into ML problems with clear objectives and evaluation criteria, and awareness of when different model classes should be used.
  • Curiositydriven approach to learning new technologies and methods, with emphasis on applying machine learning to realworld scientific and engineering challenges.
  • Ability to work across a diverse range of data types.
  • Hands-on approach to collaboration and evaluation of technologies.
  • Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
  • Ability to travel 10% of the time (domestic and international).

Preferred

  • Master's Degree in relevant field.
  • Familiarity with common sensors and interpreting their physical data, and exposure to engineering test lab workflows.
  • Experience with computer vision for engineering applications.
  • Awareness of edge deployment concepts: model optimization and containerized deployment to industrial hardware.
  • Coursework or exposure to design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
  • Familiarity with version control, experiment tracking, and reproducible research practices

Working Environment

  • In-Person, Office Environment, R&D Engineering Lab

Our 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 siteHERE.

Milwaukee Tool is an equal opportunity employer.