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Nvidia Machine Learning Internship Jobs in California

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Nvidia Machine Learning Internship information

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.

What are the most commonly searched types of Nvidia Machine Learning jobs in California?

The most popular types of Nvidia Machine Learning jobs in California are:

What job categories do people searching Nvidia Machine Learning Internship jobs in California look for?

The top searched job categories for Nvidia Machine Learning Internship jobs in California are:

What cities in California are hiring for Nvidia Machine Learning Internship jobs?

Cities in California with the most Nvidia Machine Learning Internship job openings:

Senior Deep Learning Performance Architect

Nvidia

Santa Clara, CA • On-site

$196K/yr

Full-time

Re-posted yesterday


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies


Job description

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a meaningful impact in a dynamic, technology-focused company.

What you will be doing:

  • As a member of our deep learning architecture team, you will craft high performance energy efficient system and processor architectures to extend the state of the art in deep learning.

  • Prototype key deep learning and data analytics algorithms and applications.

  • Analyze trade-offs in performance, cost and power developing analytical models, simulators and test suites.

  • Analyze architecture performance and/or energy efficiency considering deep learning workloads, modeling and prototyping.

  • Collaborate across the company to guide the direction of machine learning, working with software, research and product teams.

What we need to see:

  • Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.

  • 4+ years of relevant work or research experience.

  • A strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture.

  • A strong background in high performance power efficient designs, energy efficient high performance computing, performance analysis and profiling to identify performance bottlenecks.

  • Fluency in programming languages such as Python, C, C++.

  • Experience and familiarity with GPU computing and parallel programming models.

  • You have firsthand work experience with analytical performance modeling, profiling, and analysis.

The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Today, NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as "the AI computing company."

NVIDIA is 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. Are you creative and seeking new challenges? If so, we want to hear from you! Come, join our DL Architecture team and help build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly growing field.

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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 28, 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.

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Pay

Benefits

Hours and flexibility

Workplace

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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