Senior Staff Engineer, Machine Learning Engineering, On-device Learning SW

Qualcomm

Confirmed live today High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$194,400–$291,600 / yr
Posted
12 days ago
Freshness
Confirmed live today
Closes
Apr 13, 2027

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $228k
This role $243k
$171k $305k
below market most similar roles pay here above market

This role pays more than 60% of similar roles. Most pay $201,812–$254,750 — the blue band above. At the midpoint, this role pays about $243k versus about $228k 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 Staff Engineer, Machine Learning Engineering, On-device Learning SW

The Senior Staff Engineer, Machine Learning Engineering ( On-device Learning SW ) joins the Qualcomm AI Research team to enable generative AI technologies on edge devices. You will develop end-to-end embedded AI software to train and finetune neural network models on leading edge hardware while optimizing for power, memory, and computation. Key responsibilities include designing ML software stacks, kernels, and runtime software, as well as collaborating with hardware teams to implement new ML operators. You will also build debugging tools and user-friendly SDKs. Required technical skills include experience with PyTorch, Python, C, and C++. The role focuses on deploying state-of-the-art models like stable diffusion and large language models onto intelligent devices including smartphones, autonomous vehicles, robotics, and IOT devices.

What you'll do

  • Develop end-to-end embedded AI software to train and finetune neural network models on Qualcomm hardware.
  • Design and enhance ML/AI software stacks, kernels, and runtime software to improve performance and power efficiency.
  • Implement high-quality solutions for new ML operators and layers to utilize next-generation AI processor capabilities.
  • Develop debugging and profiling tools to identify and resolve software performance issues.
  • Create user-friendly SDKs to facilitate rapid deployment of new customer use cases.
  • Optimize algebraic operations in algorithms specifically for hardware cores.

What we're looking for

  • Bachelor's degree in a relevant field and 6+ years of engineering experience.
  • Master's degree in a relevant field and 5+ years of engineering experience.
  • PhD in a relevant field and 4+ years of engineering experience.
  • 5+ years of experience with Machine Learning frameworks and Deep Learning (Pytorch) (preferred).
  • 5+ years of experience with programming languages suitable for machine learning such as Python, C, or C++ (preferred).
  • Strong software design, development, and debugging skills (preferred).
  • Knowledge of Android programming, algebraic operation optimization, neural network training, quantization, or Qualcomm QNN SDK (preferred).

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