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Nvidia Internships Jobs in Texas (NOW HIRING)

Senior AI Compiler Engineer, MLIR

Austin, TX

$121K - $160K/yr

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern ... A track record of mentoring early career engineers and interns is a bonus With competitive salaries ...

NVIDIA is seeking a motivated architect to work with a team in solving complex problems while ... Your history of successfully mentoring junior engineers and interns is a huge plus. Ways to stand ...

A track record of success in mentoring junior engineers and interns is a bonus. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the ...

Software Engineer (AI/ML)

Austin, TX · On-site

$110 - $170/hr

Work with vendors like Anthropic, Microsoft/Azure OpenAI, Deepgram, and NVIDIA -- testing new voice ... internships). * Strong engineering fundamentals: you write production code, instrument it, and own ...

Nvidia Internships information

What are Nvidia internships?

Nvidia internships are temporary positions offered to students and recent graduates, giving them the opportunity to work on real-world projects at Nvidia, a leading technology company known for its work in graphics processing units (GPUs), AI, and computing. Interns gain hands-on experience, mentorship from industry experts, and exposure to cutting-edge technology. These internships are typically available in areas such as engineering, software development, research, business, and marketing. Participants can work at Nvidia offices worldwide and may also benefit from networking events, workshops, and career development resources. Successful internships can often lead to full-time employment opportunities at Nvidia.

What are the key skills and qualifications needed to thrive as an Nvidia intern?

To thrive as an Nvidia Intern, you generally need a strong academic background in computer science, engineering, or a related field, along with proficiency in programming languages like C++, Python, or CUDA. Familiarity with tools such as Git, Linux, and relevant development environments, as well as coursework or certifications in machine learning or graphics, is often expected. Initiative, teamwork, and effective communication are standout soft skills that help you learn quickly and contribute to projects. These abilities are crucial for making an immediate impact, adapting to challenging tasks, and collaborating within Nvidia's innovative and fast-paced environment.

What types of projects do Nvidia interns typically work on, and how much autonomy do they have during their internship?

Nvidia interns are often assigned to real-world projects that directly contribute to the company’s products, such as developing software tools, optimizing AI models, or supporting hardware design. Interns usually work within small, specialized teams and receive mentorship from experienced engineers and researchers. While guidance is provided, interns are encouraged to take initiative, propose solutions, and manage their own tasks, fostering both independence and professional growth. Regular check-ins and collaborative meetings help interns integrate with their teams and gain valuable industry experience.

What is the difference between Nvidia Internships vs Nvidia Co-op Programs?

AspectNvidia InternshipsNvidia Co-op Programs
DurationTypically 10-12 weeks during summerUsually semester-long, 4-6 months
Work EnvironmentFull-time, project-basedPart-time, integrated with academic schedule
EligibilityUndergraduate or graduate studentsStudents enrolled in a co-op program or academic institution
Application ProcessOnline application, interviews, coding assessmentsApplication through university co-op office, interviews

Both Nvidia Internships and Nvidia Co-op Programs offer valuable industry experience, but internships are typically shorter, full-time summer roles, while co-op programs are longer, part-time roles integrated with academic schedules. Internships are ideal for students seeking quick industry exposure, whereas co-ops suit those combining work with ongoing studies.

How can I get an internship in Nvidia Internships?

To secure an internship at Nvidia, applicants should have strong technical skills in areas like programming, machine learning, or hardware design, and typically need to be enrolled in a relevant degree program. Candidates should submit an application through Nvidia's careers website, including a resume and relevant coursework or projects, and may undergo technical interviews. Internships are competitive and often require prior experience or demonstrated interest in Nvidia's technologies.

What degree is required for Nvidia internships?

Nvidia internships typically require applicants to be enrolled in a bachelor's or master's degree program related to computer science, engineering, or a similar field. Relevant skills, such as programming in C++ or Python, and a strong academic record are also important considerations for eligibility.
Infographic showing various Nvidia Internships job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution.

Senior AI Compiler Engineer, Algorithms and Code-Generation

Nvidia

Austin, TX

$121K - $160K/yr

Full-time

Re-posted 12 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies


Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are looking for an AI & Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning & AI Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AI, recommendation systems, image classification, speech recognition, etc. With the rapid advancement of AI, our DLC has been the backbone of NVIDIA's inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Time and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.

What you'll be doing:

  • Analyzing deep learning networks and developing compiler optimization algorithms.

  • Strong programming skills in CUDA including analyzing and debugging performance bottlenecks on GPUs

  • Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler techniques for AI workloads and future NVIDIA GPUs.

What we need to see:

  • Bachelor's, master's or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience.

  • 3+ years of relevant work or research experience in performance analysis and compiler optimizations.

  • Experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton, etc.).

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

  • Ability to work independently, define project goals and scope, and lead your own development efforts.

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

Ways to stand out from the crowd:

  • Proficient in CPU and/or GPU architecture especially modern Nvidia GPUs like Hopper and Blackwell

  • Understanding of deep learning models, algorithms, and frameworks, such as PyTorch, JAX.

  • GPU kernel authoring and performance analysis using tools such as Nsight Compute.

  • A track record of success in mentoring early-career engineers and interns is a bonus.

  • Track record on new hardware bring-up is a plus.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

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 July 18, 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

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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