GPU Kernel Development Engineer Fellow

Amd

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TX
Salary
$231,360–$347,040 / yr
Posted
8 days ago
Freshness
Confirmed live 2 days ago
Closes
Sep 3, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $211k
This role $289k
$143k most similar roles pay here $369k

This role pays more than 90% of similar roles. Most pay $177,250–$244,000 — the shaded band above. At the midpoint, this role pays about $289k versus about $211k for comparable roles.

Based on 240 similar postings.

Employer

About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 367 open roles on FindRole.

Listed pay typically runs $166,400–$249,600 across 367 roles with salary data.

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View all roles at Amd

At a glance

TL;DR · GPU Kernel Development Engineer Fellow

As a GPU Kernel Development Engineer (Fellow), you will join the team to define and drive end-to-end software optimization strategies aimed at achieving industry-leading performance for top-tier customers. You will be responsible for GPU architecture feature design, usage, API design, and deployment while performing external benchmarking and research to identify opportunities for improving kernel performance on machine learning products. Your daily work involves analyzing the AI software stack, collaborating with hardware, compiler, and framework teams to influence future silicon features based on evolving trends, and partnering with hyperscalers to deliver tailored optimizations. You will utilize expertise in ROCm core software, advanced algorithms, and modern model architectures including Transformer, Attention, KV Cache, quantization, speculative decoding, and FlashAttention. This role focuses on solving performance challenges within the machine learning and high-performance computing domains.

What you'll do

  • Define and drive the end-to-end software optimization strategy to achieve industry-leading performance for top-tier customers.
  • Perform external benchmarking and research to identify opportunities for improving GPU kernel performance on machine learning products.
  • Analyze and optimize GPU kernels while providing insights on optimization paths across the AI software stack.
  • Partner with customers and hyperscalers to deliver tailored architectural wins and software optimizations based on specific workload requirements.
  • Influence future silicon features by collaborating with hardware, compiler, and framework teams regarding AI workload trends.
  • Communicate with technical experts to improve ROCm applications, libraries, tools, and underlying hardware.
  • Develop high-performance ROCm core software for machine learning and high-performance computing (HPC) applications.

What we're looking for

  • Experience in GPU kernel development with a focus on compute and machine learning software.
  • Expertise in performance analysis, algorithm development, and high-performance computing (HPC).
  • Knowledge of modern model architectures including Transformer, Attention, KV Cache, quantization, speculative decoding, and FlashAttention.
  • Proven experience optimizing GPU kernels across the entire AI software stack.
  • Ability to collaborate with cross-functional teams including hardware architecture, compiler, and framework teams.
  • Ability to drive initiatives in fast-paced and ambiguous environments.
  • Bachelor’s, Master's, or PhD degree in Computer Science, Computer Engineering, or a related field.

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