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Machine Learning Biomedical Engineer Jobs in Grafton, WI

Bespoke Labs

Machine Learning Engineer

Milwaukee, WI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Varsity Tutors

Biomedical Engineering Tutor

Milwaukee, WI · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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All JobsMachine Learning Biomedical Engineer JobsMachine Learning Biomedical Engineer Jobs in Grafton, WI

Machine Learning Biomedical Engineer information

See Grafton, WI salary details

$31K

$126.6K

$190.2K

How much do machine learning biomedical engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for machine learning biomedical engineer in Grafton, WI is $126,602.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $152,400.00 per year, depending on experience, location, and employer.

What does a machine learning biomedical engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

How does a machine learning biomedical engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.

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

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

Machine Learning Biomedical Engineer jobs near you
Infographic showing various Machine Learning Biomedical Engineer job openings in Grafton, WI as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $126,602 per year, or $60.9 per hour.

Machine Learning Engineer II

Milwaukee Tool

Brookfield, WI

Full-time

Medical, Dental, Vision, Retirement

Re-posted 3 days ago

Job description

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.

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