Full-Time

Compiler Engineer – New College Grad 2026

Infrastructure

Posted on 7/20/2026

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$108k - $178.3k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Remote in USA + 3 more

More locations: Austin, TX, USA | Redmond, WA, USA | Santa Clara, CA, USA

Remote

Category
Software Engineering (1)
Required Skills
C/C++
DevOps

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Requirements
  • Recent graduate of a B.S. or M.S in Computer Science, Computer Engineering, or related field (or equivalent experience)
  • Experience with open-source compiler frameworks
  • Excellent hands-on C++ programming skills
  • Experience working with large-scale, long-lived codebases, including refactoring and restructuring efforts
  • Solid understanding of compiler internals, including IRs, passes, build systems, and toolchains
  • Familiarity with source-control–heavy workflows (e.g., downstream vs. upstream repos, patch queues, rebasing strategies)
  • Strong software engineering fundamentals with an emphasis on robust, maintainable developer infrastructure
  • Good communication and documentation skills; ability to collaborate across teams and time zones
Responsibilities
  • Reconcile and synchronize downstream compiler codebases with open-source repositories, including restructuring, refactoring, and upstreaming internal changes where appropriate
  • Lead efforts to restructure, merge, or retire internal code to reduce divergence from upstream open-source projects
  • Design and build infrastructure, tooling, and developer workflows that improve productivity, correctness, and maintainability for internal compiler engineers
  • Develop automation and developer tools to aid in rebasing, patch management, validation, and large-scale refactoring
  • Explore and apply AI-assisted tools to improve developer workflows, including code navigation, change analysis, refactoring assistance, testing, and review efficiency
  • Partner with compiler developers, architecture teams, and CI/test infrastructure teams to ensure changes scale across geographically distributed organizations
  • Serve as a technical bridge between internal compiler development and open-source ecosystems, helping shape long-term alignment strategies
Desired Qualifications
  • Direct experience reconciling or maintaining downstream forks of open-source projects
  • Experience building developer productivity tools, CI infrastructure, or large-scale automation
  • Practical experience applying AI or ML-based tools to improve engineering workflows
  • Background in GPU programming, CUDA, or parallel programming models
  • Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • Rubin delivers 5x faster inference and 3.5x faster training than Blackwell starting H2 2026.
  • Major hyperscalers Microsoft, AWS, Google Cloud, and CoreWe confirmed Vera Rubin implementation ahead of Q3 2026.
  • Rubin Ultra targets 15 ExaFLOPS FP4 inference with 1.5 PB/s NVLink bandwidth per rack in 2027.

What critics are saying

  • HBM4 scarcity from SK Hynix and Micron forces Rubin production cut to 1.5M units in 2026.
  • Kyber NVL144 rack delayed to 2028 due to TSMC 78-layer PCB yield failure, breaking annual cadence.
  • Rubin Ultra cuts HBM4E stacks to 12-Hi, delivering only 2.66x instead of 4x performance gain.

What makes NVIDIA unique

  • Vera Rubin is a six-chip extreme codesigned AI supercomputer platform, not just a GPU.
  • NVIDIA shifted to annual architecture cadence with Rubin, Ultra, and Feynman releases through 2028.
  • Vera CPU with 88 ARM cores enables per-GPU efficiency and 1/10 Blackwell operational costs.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

-1%

2 year growth

-1%
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