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Internship Deep Learning Jobs (NOW HIRING)

Nvidia

Senior Deep Learning Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

A track record of success in mentoring junior engineers and interns is a bonus. With highly ... Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

A track record of success in mentoring junior engineers and interns is a bonus. With highly ... Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

A track record of success in mentoring junior engineers and interns is a bonus. With highly ... Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

Nvidia

Senior Deep Learning Compiler Engineer - XLA

Austin, TX · On-site

$103K - $142K/yr

A history of mentoring junior engineers and interns is a bonus. Ways to stand out from the crowd: Experience working deep learning frameworks such as JAX, PyTorch or TensorFlow. Extensive experience ...

Nvidia

Senior Deep Learning Compiler Engineer - XLA

OR · On-site +1

$104K - $143K/yr

A history of mentoring junior engineers and interns is a bonus. Ways to stand out from the crowd: Experience working deep learning frameworks such as JAX, PyTorch or TensorFlow. Extensive experience ...

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How much do internship deep learning jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for internship deep learning in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is an internship in deep learning?

An internship in deep learning is a temporary position, typically offered to students or recent graduates, where individuals gain practical experience working on projects involving neural networks, machine learning algorithms, and AI applications. Interns often assist with data preparation, model training, evaluation, and sometimes contribute to research or development of deep learning solutions. This role helps interns develop technical skills, gain exposure to real-world problems, and build a foundation for a career in artificial intelligence or related fields.

What types of projects or tasks can I expect to work on during a deep learning internship?

As a Deep Learning intern, you can typically expect to work on a variety of hands-on projects such as data preprocessing, model development, and performance evaluation. You may contribute to building and testing neural networks, experimenting with architectures like CNNs or RNNs, and assisting in preparing datasets for training. Collaboration with data scientists, engineers, and other interns is common, providing opportunities to learn best practices in model deployment and documentation. This role offers a valuable chance to gain practical experience in applying theoretical knowledge to real-world problems.

What are the key skills and qualifications needed to thrive in a deep learning internship, and why are they important?

To thrive in a Deep Learning Internship, you need a strong foundation in mathematics, programming (especially Python), and machine learning concepts, typically supported by ongoing or completed studies in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience using tools like Jupyter Notebook are highly valued. Strong problem-solving skills, curiosity, and effective communication help interns stand out when working on complex projects and collaborating with teams. These skills and qualities are crucial for efficiently developing, testing, and explaining deep learning models in a fast-evolving field.

What is the difference between Internship Deep Learning vs Data Science Intern?

AspectInternship Deep LearningData Science Intern
Required SkillsMachine learning, neural networks, programming (Python, TensorFlow)Statistics, data analysis, programming (Python, R)
Work EnvironmentResearch-focused, AI/ML teams, tech companiesBusiness analytics, data analysis teams, various industries
Common Employer UsageTech firms, AI startups, research labsConsulting firms, tech companies, finance, healthcare

Internship Deep Learning roles focus on developing neural networks and AI models, often in research or tech environments. Data Science Internships involve analyzing data, creating insights, and supporting decision-making across diverse industries. Both internships require programming skills, but Deep Learning emphasizes AI-specific knowledge, while Data Science covers broader data analysis skills.

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Infographic showing various Internship Deep Learning 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 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Senior Deep Learning Compiler Engineer

Santa Clara, CA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

$122K - $168K/yr

Full-time

Re-posted 17 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world
We are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.
What you'll be doing:
  • Analyzing deep learning networks and developing compiler optimization algorithms.
  • Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.
  • Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.

What we need to see:
  • Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience
  • 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
  • Ability to work independently, define project goals and scope, and lead your own development efforts.
  • Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
  • Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.

Ways to stand out from the crowd:
  • Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.
  • Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.
  • Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.
  • GPU kernel generation with high performance and fast build time.
  • A track record of success in mentoring junior engineers and interns is a bonus.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 4, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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