Principal AI Performance Engineer

Arm Holdings

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CA
Salary
$262,700–$355,400 / yr
Posted
8 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k
This role $309k
$136k most similar roles pay here $379k

This role pays more than 94% of similar roles. Most pay $196,750–$255,000 — the shaded band above. At the midpoint, this role pays about $309k versus about $226k for comparable roles.

Based on 240 similar postings.

Employer

About Arm Holdings

Arm Holdings plc is a leading British semiconductor and software design firm, established in 1990 and recognized for developing energy-efficient processor architectures that power nearly all smartphones and a vast range of IoT and computing devices.

Arm Holdings currently has 106 open roles on FindRole.

Listed pay typically runs $209,100–$282,900 across 106 roles with salary data.

Most-posted roles

View all roles at Arm Holdings

At a glance

TL;DR · Principal AI Performance Engineer

As a Principal AI Performance Engineer, you will join the engineering organization to help customers achieve best-in-class inference performance and power efficiency for production AI models running on Arm technology. You will develop kernel-level implementations across various DNN models, create production-quality reference implementations, and produce technical content focused on performance. The role involves diagnosing complex performance challenges and translating technical insights into recommendations for leadership to influence IP and software roadmaps. To succeed, you must possess deep knowledge of parallel computing, memory hierarchies, and optimization techniques for DNNs. You will utilize Python, C++, Triton, CUDA, and various profiling tools to optimize workloads. This position serves as a critical technical bridge between customers and internal teams, specifically addressing the challenge of optimizing AI performance on edge devices within the Arm ecosystem.

What you'll do

  • Develop kernel-level and system-level implementations to optimize AI workloads for Arm technology.
  • Optimize DNN models for best-in-class performance and power efficiency on edge devices.
  • Create production-quality reference implementations and technical documentation for customer use.
  • Act as a technical bridge between customers and internal teams to resolve complex performance issues.
  • Translate complex technical challenges into clear insights for engineers and senior leadership.
  • Influence Arm’s IP and software roadmaps based on real-world customer usage data.
  • Use profiling and analysis tools to diagnose and resolve hardware-specific performance bottlenecks.

What we're looking for

  • Experience optimizing DNNs in Triton, CUDA, or other kernel-level programming languages.
  • Deep understanding of parallel computing, memory hierarchies, and performance optimization techniques for DNNs.
  • Strong programming skills in Python and C++.
  • Experience with modern AI frameworks, execution models, and profiling/analysis tools.
  • Strong communication and interpersonal skills to translate technical challenges for various audiences.
  • Experience in a customer-facing or field engineering environment (preferred).
  • Experience within the Arm ecosystem (preferred).
  • Background in AI performance optimization for edge devices (preferred).

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