Senior AI Compiler Engineer, Algorithms and Code-Generation

Nvidia

Confirmed live today Low trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TX
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 105 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $192k

This role $197k

$139k $252k

below market most similar roles pay here above market

This role pays more than 64% of similar roles. Most pay $161,375–$222,500 — the blue 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 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior AI Compiler Engineer, Algorithms and Code-Generation

Role Posting Log in to save

JOB TITLE: Senior AI Compiler Engineer, Algorithms and Code-Generation The Senior AI Compiler Engineer, Algorithms and Code-Generation joins the Deep Learning & AI Compiler team to develop the backbone of the inference engine for data centers, personal devices, automotive, and robotics. You will analyze deep learning networks to develop compiler optimization algorithms, define public APIs, and implement compiler techniques for AI workloads on future NVIDIA GPUs. Key responsibilities include performance analysis, debugging bottlenecks, and ensuring fast build times and reduced memory footprints for Ahead-of-Time and Just-in-Time systems. The role requires proficiency in C/C++, Python, and CUDA, along with experience in compiler technologies like MLIR, LLVM, XLA, and Triton. Candidates should understand CPU and GPU architectures, specifically Hopper and Blackwell, and possess experience with deep learning frameworks like PyTorch and JAX.

Skills

CUDA C++ Python LLVM MLIR XLA Triton PyTorch JAX GPU Architecture Nsight Compute Compiler Optimization Deep Learning Inference

What you'll do

Analyze deep learning networks to develop compiler optimization algorithms.
Debug and analyze performance bottlenecks on GPUs using CUDA.
Define public APIs for the Deep Learning & AI Compiler.
Implement compiler techniques specifically for AI workloads and future NVIDIA GPUs.
Optimize compiler performance for fast build times and reduced memory footprints.
Develop Ahead-of-Time and Just-in-Time compiler features.
Design and implement software using C++, Python, and compiler technologies like MLIR or LLVM.

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 and software design skills, including debugging, performance analysis, and test design.
Strong programming skills in CUDA, including analyzing and debugging performance bottlenecks on GPUs.
Ability to work independently, define project goals and scope, and lead development efforts.
Strong interpersonal skills and the ability to work in a dynamic product-oriented team.
Proficiency in CPU and/or GPU architecture, especially modern Nvidia GPUs like Hopper and Blackwell (preferred).

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