NVIDIA 2026 Internships: Systems Software Engineering at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Technology, SemiconductorsIndustries

Requirements

Pursuing Bachelor's, Master's, or PhD degree in a relevant or related field
Strategic, ambitious, hard-working, and creative mindset
Passion for tackling challenging problems in accelerated computing, AI, and related areas
Course or internship experience in areas such as: Operating Systems (Threads, Process Control, Memory/Resource Management, Virtual Memory), Multithreaded Debugging, Linux Kernel Development, RTOS Development on Embedded Platforms, Data Structures & Algorithms (time/space complexity), Computer Networking (TCP/IP, OSI Model, Sockets), Computer Architecture, Real-Time Systems Development, Device Driver Programming, Game Console Middleware, Low-Level Library Development, 3D/2D Graphics Theory/Implementation/Optimizations, Simulation or Emulation, Compiler Construction, Advanced Algorithms and Data Structures, Compiler Development, Open Source Programming, High-Performance Computing (HPC), Automation Tools (XLA, TVM, Halide), Open Source Tools (CLANG, LLVM, gcc), Embedded Systems (Processors, Firmware, Input/Output Devices and Memory), Real-Time Performance, Low-Level Development, Computer Systems Software

Responsibilities

Defining, designing, and developing integrated (e.g., Jetson Orin) and discrete (e.g., Hopper H100) GPU system software components (e.g., runtime, math libraries) with focus on power and performance
Creating architecture and design specifications for systems software
Designing and implementing OpenGL, OpenGL ES, and Vulkan graphics drivers, platform support, and conformance tests to support new hardware features in collaboration with software, hardware, architecture, and support teams
Training and debugging issues within the Tegra graphics software stack
Working on deep-learning compiler technology, spanning architecture design and support through functional languages
Investigating problems or optimization opportunities within the Compiler backend, collaborating with global compiler, hardware, and application teams to oversee improvements and problem resolutions
Supporting development of firmware run on embedded microcontrollers within GPUs, optimizing software for system robustness, performance, and security
Participating in testing new and existing firmware
Developing tools and infrastructure to improve front-end design and verification processes
Working on 12-week full-time projects with measurable business impact

Skills

Key technologies and capabilities for this role

Operating SystemsLinux Kernel DevelopmentRTOS DevelopmentMultithreaded DebuggingData Structures & AlgorithmsComputer NetworkingTCP/IPSocketsOpenGLOpenGL ESVulkanGPU System SoftwareEmbedded Platforms

Questions & Answers

Common questions about this position

What is the duration and type of this internship?

The internship is a 12-week full-time program.

What degree levels are required for this internship?

NVIDIA is looking for students pursuing Bachelor's, Master's, or PhD degrees within a relevant or related field.

What skills or experience are needed for the Systems Software internship?

Course or internship experience related to Operating Systems (Threads, Process Control, Memory/Resource Management, Virtual Memory), Multithreaded Debugging, Linux Kernel Development, RTOS Development on Embedded Platforms, Data Structures & Algorithms (time/space complexity), and Computer Networking (TCP/IP, OSI Model, Sockets) could be required.

What kind of qualities is NVIDIA seeking in interns?

NVIDIA seeks strategic, ambitious, hard-working, and creative individuals who are passionate about helping tackle challenges no one else can solve.

How does the application process work for these internships?

Submit your resume to express interest; resumes are reviewed on an ongoing basis, and a recruiter may reach out if your experience fits one of the internship opportunities.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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