AI Systems Hardware Engineer

Qualcomm

Quick summary

Work type
On-site
Location
San Diego, CA · Austin, TX
Salary
$164,000–$246,000 / yr
Posted
1 day ago
Closes
Dec 2, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $204k
This role $205k
$152k most similar roles pay here $256k

This role pays less than 53% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $205k versus about $204k 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 558 open roles on FindRole.

Listed pay typically runs $154,000–$231,000 across 401 roles with salary data.

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At a glance

TL;DR · AI Systems Hardware Engineer

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Join Qualcomm Technologies as a senior engineer focused on optimizing AI workloads for next-generation system-technology solutions amid the slowing Moore’s law era. You will identify and address bottlenecks in state-of-the-art and emerging AI workloads such as mixture-of-experts (MoE) models, multi-tenant vector databases, and multimodal physical AI across various business units from data centers to computing devices. Your daily tasks include mapping these complex workloads onto Qualcomm’s systems using both internal and external tools, conducting what-if scenario analyses for optimizing SoC, memory, networking components, and other technology features to achieve optimal power-performance-TCO trade-offs. Success in this role requires a deep understanding of end-to-end system KPIs, proficiency in scripting languages like Python, and the ability to collaborate with high-level representatives across functional teams to drive innovative solutions.

Skills

Python Docker Kubernetes Terraform AWS CI/CD PostgreSQL Prometheus Grafana SQL C++ Java Linux Git RESTful_APIs JSON YAML Scalability Performance_Tuning

What you'll do

  • Identify system and technology bottlenecks for emerging AI workloads.
  • Map AI workloads to Qualcomm’s next-gen AI accelerator systems using tools.
  • Optimize SoC, memory, networking components for power-performance-TCO trade-offs.
  • Determine relevant AI workloads for various business units across BUs.
  • Collaborate with high-level representatives to develop implementation strategies.

What we're looking for

  • Thorough understanding of E2E system KPIs for emerging AI workloads.
  • Proficiency in scripting languages like Python to map new workloads onto Qualcomm systems.
  • Deep knowledge of state-of-the-art AI workloads across multiple business units.
  • Master's or Ph.D. in Electrical Engineering, Computer Science, or related field.
  • Ability to innovate and develop products/ processes without established objectives.
  • Strong verbal and written communication skills for complex information conveyance.
  • Deductive and inductive problem-solving skills with advanced data analysis capabilities.

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