Internship

NVIDIA Internships: 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

Internship available in Santa Clara, CA, and also offers remote work options.

Category
Full-Stack Engineering
Software QA & Testing
Software Engineering
Required Skills
Kubernetes
Python
JavaScript
React.js
Data Science
CUDA
Git
Data Structures & Algorithms
Apache Spark
Apache Kafka
Java
Operating Systems
Docker
Go
Vue.js
Ansible
C/C++
Linux/Unix
Cassandra
Requirements
  • Currently pursuing a Bachelor's, Master's, or PhD degree within Computer Engineering, Electrical Engineering, Computer Science, or a related field
  • Course or internship experience related to the following areas could be required: Relational Databases, Linear Algebra & Numerical Methods, Operating Systems (memory/resource management), Scheduling and Process Control, Hardware Virtualization
  • Course or internship experience related to the following areas could be required: Distributed Systems, Data Structures & Algorithms, Virtualization, Automation/Scripting, Container & Cluster Management, Debugging
  • Course or internship experience related to the following areas and technologies could be required: Unix/Shell Scripting, Linux, Java, JavaScript (including Node, React, Vue), C++, CUDA, OOP, Go, Python, Git, GitLab, Perforce, Kubernetes and Microservices, Schedulers (LSF, SLURM), Containers (Docker), Configuration Automation (Ansible)
  • Course or internship experience related to the following areas could be required: Data Science, Data Engineering, Open Source Data Science Tools, Open Source Libraries
Responsibilities
  • Work on projects that have a measurable impact on our business
  • Support overall architecture and design of our cloud storage infrastructure
  • Implement and troubleshoot storage and data platform tools, automating storage infrastructure end-to-end
  • Build industry leading technology by proving workflows and infrastructure, alongside a team of experts in production software development and chip design methodologies
  • Enable success for content running on the chip from application tracing and analysis to modeling, diagnostics, performance tuning, and debugging
  • Support cloud and on-premise infrastructure for backend analytics
  • Work on diverse data technologies including Kafka, ELK, Cassandra, and Spark

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

15%

1 year growth

27%

2 year growth

45%
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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