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Embedded Machine Learning Internship Jobs in Berkeley, CA

Velo3D

Machine Learning Engineer

Fremont, CA

$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 ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

  • Medical

  • Retirement

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 ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

  • Medical

  • Retirement

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 ...

Atoms

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 ...

Atoms

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 ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

What we're looking for * 4+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

Staff Machine Learning Engineer

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

What we're looking for * 10+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

ATOMS Careers page

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

What we're looking for * 4+ years of non-internship professional MLE experience. * Deep expertise ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

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 ...

Orchard

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will develop solutions for machine learning and computer vision ... Preferred : • Experience deploying & optimizing ML models to run fast on embedded compute like ...

Crowe LLP

Machine Learning Intern

San Francisco, CA · On-site

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Berkeley, CA

Embedded Machine Learning Internship information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

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

As of Aug 17, 2026, the average yearly pay for embedded machine learning internship in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 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.

What are popular job titles related to Embedded Machine Learning Internship jobs in Berkeley, CA?

For Embedded Machine Learning Internship jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Internship jobs in Berkeley, CA look for?

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What cities near Berkeley, CA are hiring for Embedded Machine Learning Internship jobs?

Cities near Berkeley, CA with the most Embedded Machine Learning Internship job openings:

Embedded Machine Learning Internship jobs near you

Machine Learning Engineer Intern

Neuralink

South San Francisco, CA • On-site

$35/hr

Full-time, Internship

Medical, Dental, Vision, Retirement

Re-posted 6 days ago

Job description

About Neuralink:
We are creating devices that enable a bi-directional interface with the brain. These devices allow us to restore movement to the paralyzed, restore sight to the blind, and revolutionize how humans interact with their digital world.
Team Description:
The Brain Computer Interface (BCI) Applications Team is responsible for delivering a product that gives people with paralysis the ability to control computers, phones, gaming consoles, and robotic arms with their minds at the same speed and functionality level as able-bodied people can. Furthermore, the team is focused on restoring speech for mute individuals and enabling direct, natural silent communication with AI agents. In this role, you'll work with neuroscientists, physicians, software engineers, and electrical engineers to develop the next-generation human-ready Brain-Computer Interface (BCI).
Job Description and Responsibilities:
We are hiring a Machine Learning Engineer Intern to develop novel neural decoders to increase control speed and accuracy, improve reliability, and expand functionality of BCIs. You will play a critical role in developing machine learning solutions and driving the successful execution of projects to achieve mission critical goals. You'll work with cross-functional teams to design new BCI functionalities and novel computer user interfaces.
Required Qualifications:
  • Evidence in delivering high-impact projects either in academia or industry
  • Prior experience designing and building Machine Learning models
  • Deep understanding of machine learning concepts and fundamentals
  • Experience in analyzing complex datasets, driving insights, and communicating results in a simple and clear way to both technical and non-technical stakeholders
  • Excellent communication and collaboration skills
  • Strong coding skills, with a focus on clean, efficient, and scalable code development

Preferred Qualifications:
  • Experience working with time series or unstructured data

Expected Compensation:
The anticipated hourly rate for this position is listed below.
California Hourly Rate:
$35/Hr USD
What We Offer:
Full-time employees are eligible for the following benefits listed below.
  • An opportunity to change the world and work with some of the smartest and most talented experts from different fields
  • Growth potential; we rapidly advance team members who have an outsized impact
  • Excellent medical, dental, and vision insurance through a PPO plan
  • Paid holidays
  • Commuter benefits
  • Meals provided
  • Equity (RSUs) *Temporary Employees & Interns excluded
  • 401(k) plan *Interns initially excluded until they work 1,000 hours
  • Parental leave *Temporary Employees & Interns excluded
  • Flexible time off *Temporary Employees & Interns excluded

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