Senior AI Compiler Engineer, Algorithms and Code-Generation

Nvidia

Confirmed live 2 days ago Low trust
Remote

Quick summary

Work type
Remote
Location
Santa Clara, CAAustin, TX
Salary
$152,000–$241,500 / yr
Posted
59 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $192k
This role $197k
$132k most similar roles pay here $253k

This role pays more than 63% of similar roles. Most pay $162,000–$222,000 — the shaded band above. At the midpoint, this role pays about $197k versus about $192k for comparable roles.

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 · Senior AI Compiler Engineer, Algorithms and Code-Generation

As a Senior AI Compiler Engineer, Algorithms and Code-Generation, you will join the Deep Learning & AI Compiler team to develop compiler optimization algorithms for deep learning networks. You will be responsible for defining public APIs, performing performance optimizations, and implementing compiler techniques specifically for AI workloads and future GPUs. Your daily work involves analyzing and debugging performance bottlenecks on GPUs while ensuring the compiler delivers high inference performance, fast build times, and reduced memory footprints. The role requires proficiency in C++, Python, and CUDA, along with experience in technologies such as MLIR, LLVM, XLA, or Triton. You will address technical challenges in large language models, generative AI, and recommendation systems by optimizing the software backbone used across data centers, personal devices, automotive, and robotics platforms to support the global deep learning community.

What you'll do

  • Analyze deep learning networks and develop compiler optimization algorithms.
  • Identify and debug performance bottlenecks on GPUs using CUDA.
  • Define public APIs for the Deep Learning Compiler (DLC) platform.
  • Implement compiler techniques specifically tailored for AI workloads and future GPU architectures.
  • Optimize inference performance, build times, and memory footprints for various hardware platforms.
  • Develop software using C++, Python, and compiler technologies like MLIR or LLVM.
  • Design and implement test cases to ensure software reliability and performance.

What we're looking for

  • Bachelor’s, master’s, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience.
  • 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
  • Experience with compiler technologies such as MLIR, LLVM, XLA, or Triton.
  • Excellent C/C++ and Python programming skills including software design, debugging, and test design.
  • Strong programming skills in CUDA for analyzing and debugging performance bottlenecks on GPUs.
  • Proficiency in CPU and GPU architecture, specifically modern NVIDIA GPUs like Hopper and Blackwell.
  • Understanding of deep learning models, algorithms, and frameworks such as PyTorch or JAX.
  • Ability to work independently, define project goals, and lead development efforts in a team environment.

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