Senior System Performance Engineer, Data Center/AI

Qualcomm

Confirmed live today High trust

Quick summary

Work type: On-site
Location: San Diego, CA
Salary: $129,500–$194,300 / yr
Posted: 35 days ago
Freshness: Confirmed live today
Closes: Mar 21, 2027
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $201k

This role $162k

$116k $255k

below market most similar roles pay here above market

This role pays less than 77% of similar roles. Most pay $166,773–$235,750 — the blue band above. At the midpoint, this role pays about $162k versus about $201k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$221,900 across 550 roles with salary data.

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At a glance

TL;DR · Senior System Performance Engineer, Data Center/AI

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The Senior System Performance Engineer joins the System Performance Team to optimize and validate the performance, power efficiency, and scalability of advanced computing, AI, and datacenter platforms. This role involves analyzing and optimizing power, performance, and thermal behavior of complex systems by profiling workloads and identifying bottlenecks across SoC hardware and software architectures. You will execute performance and power analysis plans for compute, memory, storage, networking, and accelerator scenarios while developing automation, tooling, and analysis infrastructure. Key technical requirements include proficiency in Python and C/C++, knowledge of ARM SoC concepts like SMMU and GIC, and experience with memory hierarchies and cache systems. You will specifically address performance characteristics for modern AI, machine learning, and Large Language Model workloads within datacenter and high-performance computing environments.

Skills

Python C/C++ SoC AI Machine Learning LLM ARM Computer Architecture Power Analysis Distributed Computing SMMU GIC Coresight-PMU operating-system scheduling High-Performance Computing

What you'll do

Profile and analyze complex AI, machine learning, and high-performance computing workloads in emulation and software environments.
Execute performance and power analysis plans for compute, memory, storage, networking, and accelerator scenarios.
Identify optimization opportunities for power, performance, and efficiency across SoC hardware and software architectures.
Triage performance and scalability issues to determine root causes and communicate findings to stakeholders.
Evaluate emerging AI/ML and datacenter workloads to understand system behavior and identify improvements.
Develop automation, tooling, and analysis infrastructure to streamline performance investigations and improve engineering productivity.
Prepare technical documentation and reports to communicate performance findings and recommendations.

What we're looking for

Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field (preferred).
4+ years of practical post-silicon experience in power and performance analysis of complex SoCs (preferred).
Strong programming and scripting skills in Python and C/C++ (preferred).
Strong understanding of memory hierarchy, cache systems, and high-performance system interconnects (preferred).
Understanding of ARM SoC concepts and architecture specifications such as SMMU, GIC, Coresight-PMU, and various bus interface protocols (preferred).
Understanding of software power-management frameworks, operating-system scheduling, and resource-management behavior (preferred).
Knowledge of modern AI/ML and Large Language Model (LLM) workloads and their performance characteristics (preferred).
Familiarity with distributed computing, AI infrastructure, and datacenter system concepts (preferred).

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