ZipRecruiter

Log In

1

Embedded Machine Learning Internship Jobs (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Pangram

Machine Learning Engineer (Junior)

New York, NY · On-site

$135K - $150K/yr

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build ... Practical experience with deep learning: internships, undergrad or masters' level research projects ...

Pangram

Machine Learning Engineer (Junior)

Manhattan, NY · On-site

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build ... Practical experience with deep learning: internships, undergrad or masters' level research projects ...

Sanics Edu

What you'll do About the internship Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This ...

New

previous pagenext page

Showing results 21-40

All JobsInternship JobsTechnology JobsSoftware JobsSoftware Developer JobsEmbedded Machine Learning Internship Jobs

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 Sep 12, 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:

What job categories do people searching Embedded Machine Learning Internship jobs look for?

The top searched job categories for Embedded Machine Learning Internship jobs are:

What other helpful pages are available for Embedded Machine Learning Internship?

Other pages related to Embedded Machine Learning Internship:

Embedded Machine Learning Internship jobs near you
Infographic showing various Embedded Machine Learning Internship job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

New York, NY • On-site

Jane Street
Finance and Insurance • 1 - 5K employees
Learn more about Jane Streetexternal

Full-time

Re-posted 8 days ago

Job description

About the Position

Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done. Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. If you'd like to learn more, you can have a look at our Machine Learning page.

During the program, you'll work on projects mentored closely by the full-time employees who designed them. Some projects consider big-picture questions that we're still trying to figure out, while others involve building something new. You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.

The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including 1-2 dedicated to assessing ML engineering skills.

Learn more about Jane Street's internship program here.

About You

If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you'll fit right in. We don't expect you to have a background in finance-we're more interested in how you think and learn than what you currently know. You should be:

  • An undergraduate or PhD student with practical experience training an ML model, working on an ML library, or optimizing an ML workflow 
  • A top-notch programmer with a love for technology
  • Intellectually curious, collaborative, and eager to learn
  • Humble and unafraid to ask questions and admit mistakes

Apply