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Nvidia Machine Learning Internship Jobs (NOW HIRING)

Nvidia

Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership. * Mentor interns and junior researchers to develop technical growth within the team.

Nvidia

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$143K - $189K/yr

Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Nvidia

Senior Deep Learning Software Engineer

Redmond, WA · Hybrid

$137K - $180K/yr

Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Corning

... on academic, internship, personal, or professional projects. - Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn ...

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Nvidia Machine Learning Internship information

See salary details

$25.5K

$42.6K

$88K

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

As of Jul 16, 2026, the average yearly pay for nvidia machine learning internship 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 types of projects do interns typically work on during the Nvidia Machine Learning Internship?

During the Nvidia Machine Learning Internship, interns often work on real-world projects involving deep learning, computer vision, or natural language processing. These projects may include developing new models, optimizing existing algorithms, or contributing to open-source frameworks. Interns typically collaborate with experienced engineers and researchers, gaining hands-on experience while having access to state-of-the-art GPU hardware. The work environment encourages innovation and learning, and interns are often given opportunities to present their results to senior team members.

What is the difference between Nvidia Machine Learning Internship vs Data Science Internship?

AspectNvidia Machine Learning InternshipData Science Internship
Required CredentialsRelevant coursework, programming skills, possibly some machine learning certificationsStatistics, programming, data analysis skills, often a related degree
Work EnvironmentResearch labs, tech company offices, collaborative teams focused on AI/ML projectsBusiness environments, data analysis teams, cross-functional collaboration
Employer & Industry UsageTech companies, AI/ML research labs, hardware/software firms like NvidiaVarious industries including tech, finance, healthcare, and consulting

While both internships involve working with data and programming, Nvidia Machine Learning Internships focus specifically on developing and optimizing machine learning models in a hardware and AI context, whereas Data Science Internships emphasize analyzing data to derive insights across diverse industries.

What is an Nvidia Machine Learning Internship?

An Nvidia Machine Learning Internship is a temporary, hands-on program for students or recent graduates to work with Nvidia’s teams on projects related to machine learning and artificial intelligence. Interns typically assist with research, data analysis, model development, and software engineering tasks using Nvidia’s cutting-edge GPU technologies. The internship provides valuable real-world experience, mentorship from industry experts, and the opportunity to contribute to innovative AI solutions. It’s a great way to build skills, expand your professional network, and potentially secure a full-time role at Nvidia in the future.

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

To excel as an Nvidia Machine Learning Intern, you need a solid foundation in computer science, mathematics, and machine learning concepts, typically supported by progress toward a relevant degree. Familiarity with programming languages like Python, deep learning frameworks such as TensorFlow or PyTorch, and GPU computing tools (e.g., CUDA) is essential. Strong analytical thinking, problem-solving skills, and effective teamwork set standout interns apart. These competencies enable you to contribute meaningfully to advanced AI projects and collaborate efficiently within Nvidia's innovative environment.
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Nvidia Machine Learning Internship jobs near you
Senior Scientist, Synthetic Data Generation

Senior Scientist, Synthetic Data Generation

Nvidia

On-site

Full-time

Posted 5 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 at the forefront of the AI revolution, and our research is shaping the future of large language models. We are looking for a Senior Scientist to join our team and help advance our capabilities in synthetic data generation for training frontier models. You will contribute to open-source libraries within the NVIDIA NeMo ecosystem that generate synthetic datasets across text, code, structured, and multimodal data, directly feeding the pre- and post-training of LLMs such as Nemotron. This role combines hands-on software engineering with applied research in generative methods, and you will collaborate with research, engineering, product, and model teams as well as external labs.

What you'll be doing:

  • Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning, coding, structured output, and multimodal understanding.

  • Advance multimodal synthetic data generation - image, document, video, and audio - in partnership with NVIDIA's model teams.

  • Design and maintain open-source libraries and SDKs with clean APIs and strong documentation.

  • Drive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD.

  • Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership.

  • Mentor interns and junior researchers to develop technical growth within the team.

What we need to see:

  • PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.

  • A research background of 3+ years in synthetic data generation, generative modeling, multimodal machine learning, or related areas. Comparable experience is also considered.

  • Deep technical understanding of LLMs, how data shapes their pre- and post-training, and inference frameworks such as vLLM or TGI.

  • Proven track record of developing or maintaining software libraries used by a broad developer community.

  • Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar.

Ways to stand out from the crowd:

  • Open-source contributions in ML or data tooling.

  • Experience with multimodal generation or understanding (vision-language, document AI, video, or audio).

  • Building and optimizing scalable data pipelines for large-scale model training (throughput, distributed inference).

  • Experience generating data for agentic, tool-use, or reinforcement-learning post-training.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, 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 168,000 USD - 264,500 USD for Level 3, and 192,000 USD - 304,750 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 14, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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

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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

Year founded

1993

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