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Embedded Machine Learning Internship Jobs in Milwaukee, WI

Milwaukee Tool

Sr Electrical Engineer - RF/IoT

Brookfield, WI · On-site

$101K - $132K/yr

And we're pushing the limits in firmwareengineering,power electronics,embedded systems,machine learning, and the use of artificial intelligence. Behind our doors you'll be empowered every day to own ...

Generac

Senior Engine Code Engineer

Waukesha, WI · On-site

$104K - $143K/yr

... embedded software, and code validation. This position leverages CAN, ATI Vision, and Matlab ... Familiarity with machine learning and predictive analytics techniques applied to engine performance ...

Comprehensive Logistics

Forklift Operator

Milwaukee, WI · On-site

$16.25 - $19/hr

CLI is the most advanced 3PL with cutting-edge technology and machine learning to keep supply ... More than a logistics provider, CLI is a true embedded partner - ensuring your supply chain moves ...

Comprehensive Logistics

Forklift Operator

Milwaukee, WI · On-site

$16.25 - $19/hr

CLI is the most advanced 3PL with cutting-edge technology and machine learning to keep supply ... More than a logistics provider, CLI is a true embedded partner - ensuring your supply chain moves ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Milwaukee, WI

Embedded Machine Learning Internship information

See Milwaukee, WI salary details

$25.1K

$42K

$86.7K

How much do embedded machine learning internship jobs pay per year?

As of Aug 25, 2026, the average yearly pay for embedded machine learning internship in Milwaukee, WI is $41,955.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,000.00 and $45,300.00 per year, depending on experience, location, and employer.

What is an embedded machine learning internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an embedded machine learning internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

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

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.

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Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in Milwaukee, WI as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $41,955 per year, or $20.2 per hour.

Machine Learning Engineer II

Milwaukee Tool

Brookfield, WI • On-site

Full-time

Re-posted 8 days ago

Job description

Job Summary:
Milwaukee Tool is a company that invests in engineering resources to design and develop leadership in electronic capabilities. As a Machine Learning Engineer II, you will be responsible for creating and validating machine learning models while collaborating with cross-functional teams to enhance power tool solutions.
Responsibilities:
• create, develop, and validate machine learning models
• work with highly cross-functional teams to make power tool solutions
• innovate and explore new machine learning solutions to deploy into Milwaukee products
• demonstrate excellent problem-solving skills
• exhibit critical thinking and thrive under pressure in a dynamic environment
• show strong technical communication skills
• exhibit fundamental project management abilities
• maintain a proactive sense of ownership for projects and tasks
• understand how projects connect to broader initiatives
Qualifications:
Required:
• Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.
• 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)
• Solid 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).
Preferred:
• 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
Company:
Milwaukee Tool manufactures electric power tools and accessories. It is a sub-organization of Techtronic Industries. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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