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Nvidia Machine Learning Internship Jobs in Pflugerville, TX

Nvidia

Principal Graphics Developer Tools Engineer

Austin, TX · On-site

$138K - $171K/yr

... machine learning or generative AI techniques to software development workflows. * Contributions to game engines, graphics middleware, graphics SDKs, or open-source graphics projects. NVIDIA is widely ...

Nvidia

Senior Hardware SoC Architect

Austin, TX · On-site

NVIDIA is developing processor and system architectures that are at the forefront of accelerating machine learning, automotive and high-performance computing applications. We are building the most ...

Nvidia

Senior Software Engineer - Local AI

Austin, TX · On-site

$121K - $160K/yr

Understanding modern techniques in Machine Learning, Deep Neural Networks, and Generative AI with ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

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Nvidia Machine Learning Internship information

See Pflugerville, TX salary details

$24K

$40.1K

$82.8K

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

As of Aug 21, 2026, the average yearly pay for nvidia machine learning internship in Pflugerville, TX is $40,056.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,600.00 and $43,300.00 per year, depending on experience, location, and employer.

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 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 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 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 job categories do people searching Nvidia Machine Learning Internship jobs in Pflugerville, TX look for?

The top searched job categories for Nvidia Machine Learning Internship jobs in Pflugerville, TX are:

What cities near Pflugerville, TX are hiring for Nvidia Machine Learning Internship jobs?

Cities near Pflugerville, TX with the most Nvidia Machine Learning Internship job openings:

Nvidia Machine Learning Internship jobs near you

Senior Security Engineer, RTOS and Virtualization

Nvidia

Austin, TX • On-site

$113K - $155K/yr

Full-time

Posted 9 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle.

Within NVIDIA DRIVE Software, the Hypervisor and RTOS Team contributes significantly to NVIDIA's advancement in artificial intelligence and autonomous vehicles. Our mission is to manage system resource sharing and separation while fulfilling real-time, safety, and security needs. We design Hypervisor and RTOS focusing on automotive quality, safety, and security required by the real-time, highly reliable system parts of leading Autonomous Vehicles. We are hiring now for the position of Senior Security Engineer, RTOS and Virtualization

What you'll be doing:

  • Lead security engineering for RTOS, hypervisor, and embedded virtualization technologies across design, implementation, review, and verification.

  • Collaborate on CPU and SoC architecture, including privilege levels, memory protection, DMA, interrupts, boot flows, debug controls, and hardware isolation.

  • Build and implement defensive features such as strong partitioning, least-privilege access, secure communication, fault containment, secure updates, and recovery from malicious inputs.

  • Perform threat modeling and automotive TARA, and connect risks, mitigations, requirements, tests, and evidence to security and safety standards.

  • Review low-level C/C++ code, investigate vulnerabilities, build fuzzing and security test infrastructure, and drive fixes into production.

What we need to see:

  • 8+ years of hands-on experience in systems, embedded, platform, product, or automotive security.

  • BSEE/ BSCS degree or equivalent experience

  • Experience securing RTOS, hypervisor, kernel, firmware, boot, driver, or other privileged software.

  • Strong C/C++ skills, with focus on memory safety, concurrency, resource ownership, privilege boundaries, and isolation.

  • Familiarity with CPU and SoC security concepts including MMU/SMMU or IOMMU, DMA, interrupts, boot, debug, and hardware-backed isolation.

  • Experience with threat modeling, vulnerability analysis, exploitability assessment, fuzzing, static or dynamic analysis, and security remediation.

  • Familiarity with automotive cybersecurity, safety, or process standards such as ISO/SAE 21434, UN R155, ISO 26262 interfaces, or Automotive SPICE.

Ways to stand out from the crowd:

  • Drove adoption of Rust, Ada/SPARK, formal methods, or other memory-safe and analyzable systems approaches.

  • Built capability-based or ownership-based security models for low-level systems.

  • Built security automation, fuzzing infrastructure, review agents, or AI-assisted tools used by engineering teams.

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 August 15, 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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