Senior Performance Compiler Engineer

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Redmond, WATXWACASanta Clara, CASeattle, WA
Salary: $184,000–$287,500 / yr
Employment: Full-time
Posted: 8 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $206k

This role $236k

$146k $303k

below market most similar roles pay here above market

This role pays more than 82% of similar roles. Most pay $177,250–$235,750 — the blue band above. At the midpoint, this role pays about $236k versus about $206k 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 Performance Compiler Engineer

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JOB TITLE: Senior Performance Compiler Engineer - Triton The Senior Performance Compiler Engineer joins the team to work on the open-source Triton compiler project, focusing on improving AI performance on NVIDIA GPUs. The role involves investigating future GPU hardware architectures and programming models to identify optimization opportunities for advanced algorithms like attention sinks and MoEs. Key responsibilities include designing and implementing compiler technology using MLIR to optimize high-level kernel descriptions written in Triton's Python DSL. The engineer will generate efficient low-level GPU code, utilizing inline PTX for hand-tuning critical paths. Required skills include C++, performance analysis, debugging, and parallel programming using CUDA, OpenCL, or OpenMP. The work addresses the technical challenge of accelerating training and inference for large language models and other high-impact AI applications through deep compiler and hardware optimization.

Skills

Triton MLIR C++ CUDA PTX Python OpenCL OpenMP TVM High-Performance Computing Parallel Programming Computer Architecture Assembly BLAS

What you'll do

Investigate future NVIDIA GPU hardware architectures and programming models.
Analyze advanced AI algorithms and numerics to identify new optimization opportunities.
Design and implement compiler technology using MLIR to optimize high-level kernel descriptions.
Generate efficient low-level GPU code from Triton's Python DSL.
Use inline PTX to hand-tune critical code paths and extract peak hardware performance.
Execute an iterative optimization process across kernels and compilers to achieve maximum efficiency.
Influence future products by collaborating with hardware architects and the CUDA compiler team.

What we're looking for

Bachelor, Masters, or Ph.D. degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or a related field.
8+ years of relevant industry experience in software development.
Demonstrated strong C++ programming and software design skills with an emphasis on performance analysis and debugging.
Experience in parallel programming, including CUDA/OpenCL GPU programming or other parallel models such as OpenMP.
Solid understanding of computer architecture and hands-on experience with assembly-level programming.
Experience in tuning BLAS or deep learning library kernels (preferred).
Background in numerics and linear algebra (preferred).
Experience with machine learning compilers like TVM or MLIR (preferred).