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Internship Machine Learning Hardware Jobs (NOW HIRING)

Sr. Staff, Engineer

San Diego, CA · On-site

$110K - $152K/yr

Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software. Minimum Qualifications: • ...

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software. Minimum Qualifications: • ...

They are seeking a Machine Learning Engineer to design and develop machine learning and AI ... Preferred : • Internship, research, or project experience applying ML to real-world or research ...

Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software. Minimum Qualifications: • ...

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Showing results 1-20

Internship Machine Learning Hardware information

See salary details

$25.5K

$42.6K

$88K

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

As of Jun 13, 2026, the average yearly pay for internship machine learning hardware 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 the difference between Internship Machine Learning Hardware vs Internship Data Scientist?

AspectInternship Machine Learning HardwareInternship Data Scientist
Required CredentialsBasic knowledge of hardware, electronics, and programmingStatistics, programming, and data analysis skills
Work EnvironmentHardware labs, electronics workshops, manufacturing settingsOffice, data analysis environments, cloud platforms
Employer & Industry UsageTech companies, hardware manufacturers, research labsTech firms, finance, healthcare, consulting
Common Search & Comparison IntentUnderstanding hardware-focused roles in ML projectsData analysis and modeling roles in ML

Internship Machine Learning Hardware focuses on developing and optimizing hardware components for ML systems, while Internship Data Scientist emphasizes analyzing data and building models. Both roles are essential in AI development but differ in skills, environment, and industry application.

What is an Internship in Machine Learning Hardware?

An Internship in Machine Learning Hardware is a temporary position for students or recent graduates to gain hands-on experience working with the physical components and systems that enable machine learning applications. Interns typically assist in designing, testing, and optimizing hardware such as GPUs, TPUs, or custom accelerators that run machine learning algorithms efficiently. This role often involves collaboration with software engineers and researchers to improve the performance and energy efficiency of machine learning models. The internship provides valuable exposure to both hardware engineering and the rapidly evolving field of artificial intelligence.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Hardware, and why are they important?

To thrive as an Internship Machine Learning Hardware, you need a solid foundation in computer engineering, electrical engineering, or computer science, with coursework or experience in machine learning and hardware design. Familiarity with hardware description languages (like Verilog or VHDL), Python, C++, and tools such as TensorFlow, PyTorch, or FPGA development environments is typically required. Strong problem-solving abilities, eagerness to learn, and effective teamwork and communication skills help interns excel in multidisciplinary environments. These competencies are crucial for contributing to hardware-accelerated machine learning solutions and collaborating efficiently with engineering teams.

What kinds of projects and responsibilities can I expect during an Internship in Machine Learning Hardware?

As an intern in Machine Learning Hardware, you can expect to work on tasks such as benchmarking hardware performance for AI workloads, supporting the development and testing of new accelerator architectures, and optimizing hardware-software integration for machine learning models. You'll often collaborate with both hardware engineers and machine learning researchers, gaining exposure to the entire workflow from design to deployment. These internships typically provide hands-on experience with tools like FPGA, ASIC simulation environments, or specialized ML hardware platforms, and offer opportunities to contribute to real-world product development and research.
More about Internship Machine Learning Hardware jobs
What cities are hiring for Internship Machine Learning Hardware jobs? Cities with the most Internship Machine Learning Hardware job openings:
What are the most commonly searched types of Machine Learning Hardware jobs? The most popular types of Machine Learning Hardware jobs are:
What states have the most Internship Machine Learning Hardware jobs? States with the most job openings for Internship Machine Learning Hardware jobs include:
Infographic showing various Internship Machine Learning Hardware job openings in the United States as of June 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Mechanical Engineer, Annapurna Labs, Machine Learning Hardware

Mechanical Engineer, Annapurna Labs, Machine Learning Hardware

Amazon

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,846 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Annapurna Labs (our organization within Amazon) 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.
As a member of the Machine Learning Acceleration team you'll be responsible for the design and optimization of hardware in our data centers. You'll provide leadership in the application of new technologies to large scale server deployments in a continuous effort to deliver a world-class customer experience. This is a fast-paced, intellectually challenging position, and you'll work with thought leaders in multiple technology areas. You'll have high standards for yourself and everyone you work with, and you'll be constantly looking for ways to improve your products performance, quality and cost. We're changing an industry, and we want individuals who are ready for this challenge and want to reach beyond what is possible today.
Key job responsibilities
As a Thermal/Mechanical Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of AWS users.
About the team
In 2015, Annapurna Labs was acquired by Amazon Web Services (AWS). Since then, we have accelerated its innovation and developed a number of products that benefit cloud customers, including AWS Nitro technology, Inferentia custom Machine Learning chips, and AWS Graviton2 processors.
Annapurna Labs is a silicon/system and software organization that is delivering all the chips used by AWS customers. Today this includes: Graviton, driving innovation for general purpose compute; Nitro, driving networking and storage scale, security and Hypervisor offload, and Machine Learning (ML) Trainium and Inferentia that are enabling customers to train and run GenAI applications permanently while keeping costs under control.
BASIC QUALIFICATIONS
- BS or MS degree in Mechanical/Thermal Engineering
- 3+ years industry experience in Mechanical and Thermal design of Systems
- Experience in thermal and performance measurements and characterization on SoCs, Servers, and Systems
- 3+ years of experience SoC Thermal modelling and IC package transient thermal response
- Experience with Chip package, System Mechanical & Thermal design for air-cooled and liquid-cooled systems
- Collaborate effectively with teams spanning multiple sites and develop detailed specifications for product teams to use
- Work with ODMs, heatsink vendors, and internal design teams on cross-boundary triaging, debugging, and resolving issues across organization
PREFERRED QUALIFICATIONS
- Knowledge of SoC thermal/mechanical design methodology, power modeling and thermal analysis techniques
- Tool Familiarity: Ansys Icepak, FloTherm, Cadence Celsius, PTC Creo, and Solidworks
- Programming experience: Bash script, Shell script, Linux, Python, and Lua. Familiarity with working in Linux environment is an added advantage
- Working knowledge on fans, valves, chillers, and CDUs
- Knowledge of various types of technologies used for Heatsink solutions, Thermal Interface Materials (TIMs) and liquid cooling technologies
- Develop detailed CFD and compact RC models for SoC and Package thermal analysis
- Knowledge of hardware and software based thermal / power management control algorithms
- Optimize thermal solutions under PPA and system design constraints
- Simulate and prototype thermal control strategies
- Validate thermal models through power/thermal measurements on Hardware
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Austin - 136,000.00 - 184,000.00 USD annually
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually

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About Amazon

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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