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Nvidia Machine Learning Internship Jobs in California

Nvidia

Senior Machine Learning Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

Intelligent machines powered by Artificial Intelligence computers that can learn, reason, and ... NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of ...

Nvidia

Senior Machine Learning Engineer

Santa Clara, CA

$143K - $189K/yr

Intelligent machines powered by Artificial Intelligence computers that can learn, reason, and ... NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of ...

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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.
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Nvidia Machine Learning Internship jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Nvidia

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Posted 20 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 245 rated software companies

Job description

Intelligent machines powered by Artificial Intelligence computers that can learn, reason, and interact with people are no longer science fiction. Today, a self-driving vehicle powered by AI can meander through a country road at night and find its way. NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots, and self-driving vehicles that can perceive and understand the world.

Our team is building the machine learning backbone of the Perception component for NVIDIA DRIVE AV. We are seeking the best Machine Learning Engineers with a background in computer vision, LiDAR & camera perception, and AI infrastructure who are passionate about solving the hardest problems for self-driving cars. Are you interested in inventing human-level AI for perception in the unconstrained world under any conditions? If so, join us!

What You'll Be Doing:

  • Model Development: Design, train, and optimize innovative machine learning models for LiDAR perception (e.g., road element detection, semantic segmentation, tracking).

  • Develop and coordinate entire ML workflows, covering data pipelines, model training, model metrics, continuous performance instrumentation, and reporting.

  • Productization: Take ML models and algorithms from initial evaluation and experimentation all the way to shipping them as part of the NVIDIA DRIVE AV platform, developing highly efficient product code in C++.

  • Innovation: Keep track of the latest developments in machine learning, and incorporate techniques that improve platform performance.

  • Collaborate with LiDAR/camera teams, developers, engineers, and managers to turn complex ideas into reliable solutions for autonomous driving.

What We Need to See:

  • BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.

  • 6+ years of relevant proven industry experience applying machine learning to address real-world problems.

  • Strong C++ and Python programming and debugging skills with experience in developing for large, complex systems.

  • Deep practical experience applying machine learning to lidar/camera perception in automotive or related fields.

  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and a strong understanding of the mathematical foundations of ML.

  • Building and sustaining training and essential metric workflows for large-scale datasets.

  • Excellent communication and analytical skills. Self-motivated drive to solve hard problems.

Ways to Stand Out From the Crowd:

  • LiDAR or Camera Perception Experience: Proven track record of developing and shipping deep learning models for LiDAR/Camera in a production environment.

  • Advanced Model Knowledge: Familiarity with modern network architectures like Transformers and their application to visual recognition tasks.

  • AV Production Experience: A history of delivering ML features and models into a production autonomous vehicle stack or a related robotics product.

  • Performance Optimization: Experience with model optimization for real-time inference on embedded or automotive platforms (e.g., using TensorRT).

We believe that realizing self-driving vehicles will be a defining contribution of our generation (e.g., traffic accidents are responsible for ~1.25 million deaths per year worldwide). We have the funding and scale, but we need your help on our team. NVIDIA is widely considered to be one of the technology world's most desirable employers with some of the most brilliant and talented people in the world working here. If you're creative and autonomous, 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 184,000 USD - 287,500 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 July 12, 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

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

Year founded

1993

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