Principal AI/ML Platform Architect Engineer

Qualcomm

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$200,800–$301,200 / yr
Posted
15 days ago
Freshness
Confirmed live yesterday
Closes
Feb 23, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $222k
This role $251k
$165k most similar roles pay here $316k

This role pays more than 73% of similar roles. Most pay $189,462–$254,750 — the shaded band above. At the midpoint, this role pays about $251k versus about $222k 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 623 open roles on FindRole.

Listed pay typically runs $148,300–$222,500 across 603 roles with salary data.

Most-posted roles

View all roles at Qualcomm

At a glance

TL;DR · Principal AI/ML Platform Architect Engineer

AI/ML Platform Architect - Engineer, Principal joins the Machine Learning Engineering team to drive AI system performance and power enhancements across software and hardware stacks for Snapdragon platforms. This role involves designing joint HW-SW architectures, identifying bottlenecks in machine learning algorithms, and developing on-device components for enterprise agentic AI workflows. The candidate will work on optimizing AI models for Windows PCs, ensuring high developer experience while meeting security requirements. Key responsibilities include analyzing pre-silicon predictions, creating reference implementations, and proposing features for next-generation SoCs. Required expertise includes Python, C++, and deep knowledge of TensorFlow, PyTorch, GPU/NPU programming, and parallel computing. The role addresses the technical challenge of delivering high-performance AI functionality in domains like Computer Vision, Audio, and Generative AI while optimizing power consumption across various hardware acceleration technologies for mobile and desktop environments.

What you'll do

  • Drive AI system performance and power enhancements across the software and hardware stacks for Snapdragon platforms.
  • Analyze bottlenecks in end-to-end machine learning workloads through simulation and on-device characterization.
  • Correlate and tune AI algorithms against pre-silicon predictions to ensure accurate performance targets.
  • Design and implement on-device components for enterprise agentic AI workflows and productivity tools.
  • Develop high-performance reference implementations, tools, and documentation for third-party application developers.
  • Propose new features and designs for next-generation SoCs to reduce system performance bottlenecks.
  • Optimize AI applications on Windows using processor-specific libraries and primitives for GPU and NPU hardware.

What we're looking for

  • Bachelor's degree in Computer Science or Engineering with 8+ years of experience, OR Master's with 7+ years, OR PhD with 6+ years.
  • At least 15 years of experience in High Performance Computing System Engineering or Software.
  • At least 5 years of experience in AI system optimization.
  • Proficiency in programming languages such as Python and C++.
  • Experience optimizing AI applications on Windows using GPU and NPU specific tools and libraries.
  • Strong understanding of AI frameworks like TensorFlow and PyTorch, along with GPU/NPU programming and parallel computing.
  • Knowledge of computer architecture, embedded systems, and state-of-the-art Agentic AI.
  • Strong software engineering principles and experience with version control and agile project management.

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