Internship

NVIDIA 2025 Internships: Systems Software Engineering

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$18 - $71Hourly

Remote in USA + 1 more

More locations: Santa Clara, CA, USA

Category
Backend Engineering
Embedded Engineering
Software Engineering
Required Skills
Bash
CUDA
Apache Spark
Operating Systems
Perl
C/C++
Linux/Unix
Requirements
  • Currently pursuing a Bachelor's, Master's, or PhD degree within Computer Engineering, Electrical Engineering, Computer Science, or a related field
  • C, C++, CUDA, x86, ARM CPU, GPU, Linux, Perl, Bash/Shell Scripting
  • Operating Systems (Threads, Process Control, Memory/Resource Management, Virtual Memory)
  • Formal Verification Tools (Spark, Frama-C)
  • Linux Kernel Development
  • Multi-Threaded or Multi-Process Programming
  • Open Source Tools (CLANG, LLBM, gcc)
  • Testing Production/Automation Tools (XLA, TVM, Halide)
  • Microprocessor Fundamentals (Caches, Buses, Memory Controllers, DMA, etc.)
Responsibilities
  • Defining, designing, and developing integrated and discrete GPU system software components with focus on power and performance, as well as creating architecture and design specifications
  • Designing and implementing of OpenGL, OpenGL ES, and Vulkan graphics drivers, platform support, and conformance tests to support new hardware features in collaboration with other software, hardware, architecture, and support teams
  • Training and debugging various issues within the Tegra graphics software stack
  • Working at the center of deep-learning compiler technology, spanning architecture design and support through functional languages
  • Investigating problems or optimization opportunities within the Compiler backend by working with global compiler, hardware, and application teams to oversee improvements and problem resolutions
  • Supporting development of firmware run on embedded microcontrollers within GPUs, while optimizing software to improve system robustness, performance, and security
  • Participating in testing new and existing firmware, and developing tools and infrastructure to improve our front-end design and verification process
  • Hardening and developing secure solutions across the software stack, spanning multi-node supercomputers down to microcontrollers and security co-processors
  • Building tools and infrastructure to scale security efforts across large organizations and codebases with millions of lines of code

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, such as GPUs, are essential for high-performance computing and artificial intelligence applications. NVIDIA's GPUs work by processing large amounts of data simultaneously, making them ideal for tasks like gaming graphics and complex computations in AI and machine learning. Unlike many competitors, NVIDIA focuses on both hardware and software solutions, offering cloud-based services that enhance the capabilities of their products. The company's goal is to drive innovation in AI and HPC, providing advanced solutions that cater to a wide range of clients, from gamers to researchers and enterprises.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

13%

1 year growth

25%

2 year growth

42%
Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA's diverse investment portfolio offers employees exposure to cutting-edge technologies and industries, fostering a dynamic and innovative work environment.
  • The company's strategic acquisitions and partnerships provide opportunities for professional growth and cross-industry collaboration.
  • NVIDIA's strong financial backing and market leadership ensure stability and resources for continued innovation and development.

What critics are saying

  • NVIDIA's expansion into various sectors may dilute its focus and resources, potentially impacting its core GPU business.
  • The competitive landscape in AI, robotics, and autonomous vehicles is intense, posing challenges for NVIDIA to maintain its leadership position.

What makes NVIDIA unique

  • NVIDIA's strategic investments in diverse sectors like robotics, AI disease modeling, and driverless trucks highlight its commitment to pioneering technologies beyond its core GPU business.
  • The acquisition of Shoreline.io, a software startup, indicates NVIDIA's focus on enhancing its software capabilities, setting it apart from competitors primarily focused on hardware.
  • NVIDIA's involvement in significant funding rounds for companies like Mistral AI and Bright Machines showcases its influence and leadership in the AI and intelligent manufacturing sectors.

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