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Embedded Machine Learning Internship Jobs (NOW HIRING)

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

To be successful you should have 0-3 years of of professional or internship experience in machine learning, data science, or software engineering. Also proficiency in Python and familiarity with ML ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... custom embedded GPU targets. • Deep understanding of profiling tools and debugging resource ...

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Embedded Machine Learning Internship information

See salary details

$25.5K

$42.6K

$88K

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

As of Jul 8, 2026, the average yearly pay for embedded machine learning internship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 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.
More about Embedded Machine Learning Internship jobs
What cities are hiring for Embedded Machine Learning Internship jobs? Cities with the most Embedded Machine Learning Internship job openings:
What are the most commonly searched types of Embedded Machine Learning jobs? The most popular types of Embedded Machine Learning jobs are:
What states have the most Embedded Machine Learning Internship jobs? States with the most job openings for Embedded Machine Learning Internship jobs include:
Infographic showing various Embedded Machine Learning Internship job openings in the United States as of July 2026, with employment types broken down into 1% Internship, 92% Full Time, 5% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Engineer I

Machine Learning Engineer I

Milwaukee Tool

Brookfield, WI

Full-time

Medical, Dental, Vision, Retirement

Re-posted 23 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, you will be a hands-on leader tasked with deploying 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. You will 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.

This role requires excellent problem-solving skills, critical thinking, and the ability to work well under pressure in a dynamic environment. You will leverage strong technical communication skills and fundamental project management abilities to ensure clarity and alignment across teams. Additionally, you will demonstrate a strong sense of ownership for projects and tasks, with a clear understanding of how they connect to broader initiatives.

What TOOLS you'll bring with you (Required):

  • 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
  • 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
  • Ability to travel up to 10% of the time (domestic and international).

Other TOOLS you may have (Preferred):

  • Master's degree or PhD in Machine Learning or related field
  • 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
  • Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
  • Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
  • Experience working with modern software development tools and version control tools

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.