Software Engineering Intern

Nvidia

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Santa Clara, CA
Posted: 23 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $185k

$122k most similar roles pay here $248k

This listing doesn't post a salary. Most similar roles pay $134,612–$235,750.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Software Engineering Intern

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NVIDIA 2027 Internships: Software Engineering offers students pursuing a B.S., M.S., or Ph.D. in Electrical Engineering, Computer Engineering, or related fields the opportunity to join leading software teams for a twelve-week full-time internship. Interns will work on projects with measurable business impact, including developing tools, debugging complex system-level issues, building cloud storage infrastructure, and creating backend analytics systems. The role involves solving technical challenges in accelerated computing, AI, and digital twins. Candidates may utilize technologies such as C, C++, CUDA, Python, Go, Java, JavaScript, and SQL. Specific technical domains include distributed systems, operating systems, hardware virtualization, machine learning operations, and deep learning frameworks like cuDNN and TensorRT. Tools mentioned include Git, Perforce, Kubernetes, Docker, Ansible, Jenkins, and schedulers like LSF or SLURM to support infrastructure and performance tuning.

Skills

CUDA C++ Python Go Java JavaScript React Vue Kubernetes Docker Ansible Git Perforce SQL TensorRT cuDNN cuBLAS NCCL NumPy SciPy Linux Unix/Shell Scripting Microservices SLURM LSF

What you'll do

Debug complex system-level issues using tools like Jenkins.
Support the architecture and design of cloud storage infrastructure.
Implement and troubleshoot storage and data platform tools while automating infrastructure end-to-end.
Build production software and chip design methodologies to prove workflows and infrastructure.
Perform application tracing, modeling, diagnostics, performance tuning, and debugging for content running on chips.
Develop frameworks for Deep Learning including training acceleration and real-time inference.
Build infrastructure for back-end analytics.

What we're looking for

Must be actively enrolled in a university pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field.
Resume must clearly indicate the anticipated graduation date (month and year).
Experience with programming languages such as Java, JavaScript (Node, React, Vue), C, C++, CUDA, Go, or Python.
Knowledge of software development tools including Git, Perforce, Kubernetes, Docker, and Ansible.
Proficiency in SQL and Object-Oriented Programming (OOP) principles.
Experience with systems programming such as Linux, Unix/Shell Scripting, and Distributed Systems.
Familiarity with high-performance computing concepts like GPU Computing, Accelerated Computing, and CUDA.
Knowledge of machine learning frameworks and libraries including NumPy, SciPy, cuBLAS, cuDNN, and TensorRT (preferred).

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