1

Internship Deep Learning Jobs (NOW HIRING)

We are currently hiring both full-time and interns to join our R&D team. Responsibilities: * Develop deep learning models for prototyping and production purposes according to product feature request

next page

Showing results 1-20

Internship Deep Learning information

See salary details

$8

$17

$24

How much do internship deep learning jobs pay per hour?

As of Jul 15, 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 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.

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 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.
More about Internship Deep Learning jobs
What cities are hiring for Internship Deep Learning jobs? Cities with the most Internship Deep Learning job openings:
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:
Infographic showing various Internship Deep Learning job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.
Senior Research Scientist, Efficient Deep Learning

Senior Research Scientist, Efficient Deep Learning

Nvidia

Santa Clara, CA

$115K - $147K/yr

Full-time

Re-posted 6 days ago


Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies


Job description

NVIDIA is searching for an outstanding Senior Researcher working on efficient deep learning to join our learning and perception research team. We are passionate about research that pushes boundaries but also has impact in the real world. We are particularly excited about methods for post-training model optimization (pruning, quantization, NAS), efficient architecture design, adaptive/dynamic inference, resource-efficient training and fine-tuning, and so forth. You will work within an amazing and collaborative research team that consistently publishes at the top venues in computer vision and machine learning. Our existing expertise includes computer vision, deep learning, generative models, and so forth. Your contributions have the chance to create real impact on our products.

What you'll be doing:

  • Research, design and implement novel methods for efficient deep learning.

  • Publish original research. Speak at conferences and events.

  • Collaborate on research with internal team members, internal teams as well as external researchers. Mentor interns.

  • Work with product groups to transfer technology.

What we need to see:

  • A Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent experience in industrial research labs.

  • 3+ years or relevant post-graduate research experience

  • Excellent knowledge of theory and practice of computer vision methods, as well as deep learning.

  • A background in pruning, quantization, NAS, efficient backbones is required.

  • Experience with large language models and large vision-language models is a plus.

  • Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA).

  • Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.

  • An outstanding research track record and strong communications skills.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. If you're creative and collaborative researcher, 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 192,000 USD - 304,750 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 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.

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom


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