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Machine Learning Biomedical Engineer Jobs in Grafton, WI

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 ...

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 ...

Machine Learning Tutor

Milwaukee, WI ยท 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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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 Jul 8, 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 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.

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.

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.

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.
Infographic showing various Machine Learning Biomedical Engineer job openings in Grafton, WI as of July 2026, with employment types broken down into 2% Internship, 1% As Needed, 79% Full Time, 17% Part Time, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $126,602 per year, or $60.9 per hour.
Machine Learning Engineer I

Machine Learning Engineer I

Milwaukee Tool

Brookfield, WI โ€ข On-site

Full-time

Re-posted 23 days ago


Job description

Job Summary:
Milwaukee Tool is a company that values its people and culture as key to its success, focusing on innovative engineering solutions. As a Machine Learning Engineer, you will deploy machine learning models and collaborate with cross-functional teams to enhance power tool solutions, while ensuring project clarity and ownership.
Responsibilities:
โ€ข Deploy machine learning models in creative ways while working with highly cross-functional teams to make power tool solutions that change the lives of our users.
โ€ข Act as a technical expert in the creation and execution of these concepts into products, supporting the team through implementation, validation, and transfer to production.
โ€ข Leverage strong technical communication skills and fundamental project management abilities to ensure clarity and alignment across teams.
โ€ข Demonstrate a strong sense of ownership for projects and tasks, with a clear understanding of how they connect to broader initiatives.
Qualifications:
Required:
โ€ข Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
โ€ข Completed course work or specialization in Machine Learning and/or Data Science
โ€ข 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)
โ€ข Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
โ€ข Proficient developing and debugging code in Python
โ€ข Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
โ€ข Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
โ€ข Solid mathematical foundation in statistics, linear algebra, calculus and optimization
โ€ข Ability to travel up to 10% of the time (domestic and international).
Preferred:
โ€ข Masterโ€™s degree or PhD in Machine Learning or related field
โ€ข 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 are preferred
โ€ข Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
โ€ข Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
โ€ข Experience working with modern software development tools and version control tools
Company:
Milwaukee Tool manufactures electric power tools and accessories. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently Late Stage.