ZipRecruiter

Log In

1

Internship Deep Learning Jobs (NOW HIRING)

EarnIn

Machine Learning Intern

Mountain View, CA · Hybrid

$40/hr

... deep learning, language models and generative AI, programming, and data analysis to join our 12-week Machine Learning Internship Program. You will work on real-world projects, collaborate with ...

next page

Showing results 1-20

People also search for

All JobsDeep Learning JobsInternship Deep Learning Jobs

Internship Deep Learning information

See salary details

$8

$17

$24

How much do internship deep learning jobs pay per hour?

As of May 30, 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 are the key skills and qualifications needed to thrive as an Internship Deep Learning, 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 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 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 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.

More about Internship Deep Learning jobs
What are the most commonly searched types of Deep Learning jobs? The most popular types of Deep Learning jobs are:
What states have the most Internship Deep Learning jobs? States with the most job openings for Internship Deep Learning jobs include:
What job categories do people searching Internship Deep Learning jobs look for? The top searched job categories for Internship Deep Learning jobs are:
Internship Deep Learning jobs near you
Infographic showing various Internship Deep Learning job openings in the United States as of May 2026, with employment types broken down into 3% Internship, 3% As Needed, 11% Full Time, 77% Part Time, and 6% Contract. Highlights an 78% Physical, and 22% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.
Senior Deep Learning Compiler Engineer - XLA

Senior Deep Learning Compiler Engineer - XLA

Nvidia

Santa Clara, CA

$122.70K - $168.50K/yr

Full-time

Posted 2 days ago

Job description

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company".

We are looking for versatile software engineers for our XLA team. NVIDIA is at the center for the AI revolution that's transforming how people live, work, and interact with technology. Come join us to build high-performance, production-grade software that's at the core of next-generation AI systems.

What you will be doing:

In this role, develop compiler optimization algorithms for deep learning workloads. You will optimize inference and training performance for the JAX framework and the OpenXLA compiler on NVIDIA GPUs at scale. You'll collaborate with our partners in deep learning framework teams and our hardware architecture teams to accelerate the next generation of deep learning software. The scope of these efforts include:

  • Crafting and implementing compiler optimization techniques for deep learning network graphs.

  • Designing novel graph partitioning and tensor sharding techniques for distributed training and inference.

  • Performance tuning and analysis.

  • Code-generation for NVIDIA GPU backends using open-source compilers such as MLIR, LLVM and OpenAI Triton.

  • Designing user facing features in JAX and related libraries and other general software engineering work.

  • Working closely with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.

What we need to see:

  • Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience).

  • 4+ 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 effort adopting clean software engineering and testing practices.

  • Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.

  • Strong foundation in architecture of CPU, GPUs or other high performance hardware accelerators. Knowledge of high-performance computing and distributed programming.

  • CUDA or OpenCL programming experience is desired but not required.

  • Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and deep learning framework design.

  • Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. 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 with CUDA or with GPUs in general.

  • Experience with open-source compilers such as XLA, LLVM, MLIR or TVM.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

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 March 1, 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.#deeplearning
Nvidia logo

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

Year founded

1993

View All Nvidia Jobs

Apply