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Embedded Machine Learning Internship Jobs in Austin, TX

Ericsson

Baseband Developer Intern - AI Adoption

Austin, TX · On-site

$19 - $25/hr

As an intern in our team, you'll dive into the fascinating intersection of machine learning, wireless communication systems, and embedded technologies. This internship offers an exciting opportunity ...

Symbotic

Senior Embedded Software Engineer

Austin, TX · On-site

$122K - $161K/yr

As a Senior Embedded Software Engineer, you will play a key role in designing, developing, and ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

Symbotic

Senior Embedded Software Engineer

Austin, TX · Hybrid

$122K - $161K/yr

As a Senior Embedded Software Engineer, you will play a key role in designing, developing, and ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

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All JobsEmbedded Machine Learning Internship JobsEmbedded Machine Learning Internship Jobs in Austin, TX

Embedded Machine Learning Internship information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

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

As of Jun 27, 2026, the average yearly pay for embedded machine learning internship in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 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 Austin, TX as of June 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% In-person job distribution, with an average salary of $42,209 per year, or $20.3 per hour.
Sr Software Development Engineer, System and Embedded PCIe and Neuron Link

Sr Software Development Engineer, System and Embedded PCIe and Neuron Link

Amazon

Austin, TX • On-site

$130K - $171K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,891 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
We're looking to hire a Software Development Engineer that will:
- Develop mission-critical software that powers Annapurna Labs' next-generation machine learning platforms' interconnect (PCIe and Neuron Link)
- Collaborate with EC2 teams and manufacturing partners to ensure seamless system integration
- Drive end-to-end qualification processes for new hardware implementations
Technologies useful to this role include operating systems, Linux architecture, embedded systems, and control systems

Our team uses, C, C++, Lua, Bash, Python and other similar languages to develop device drivers, and develop automation software.
Key job responsibilities
As a member of the Annapurna Labs Machine Learning PCIe and Neuron Link engineering team, you will develop software to enable and monitor Annapurna accelerated compute servers and EC2 systems handling customer Machine Learning workloads in AWS Data Centers world wide. You will work closely with hardware engineers to bring up new boards, custom silicon devices, and servers for EC2 accelerated computing instances. You will provide inputs to architects on the development of custom silicon and system features

You will develop automated software test and deployment pipelines to ensure software quality, compatibility, and upgradeability.
A day in the life
Daily tasks range from A to Z - as long as it relates to a PCIe interface, we're on it. This includes programming on device interfaces using standard subsystems such as I2C and SPI, as well as working on software which integrates the server with EC2, for diagnostics and performance.
About the team
The Annapurna Labs Machine Learning PCIe and Neuron Link team is responsible for all aspects of the interconnect between accelerators for the custom Trainium AI servers.
Our team consists of hardware, software, and firmware engineers all working together to create innovative and scaleable solutions for the next-generation of Trainium AI servers


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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