Senior Engineer, Machine Learning Engineering (ML Apps)

Qualcomm

Confirmed live today Trusted

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$140,800–$211,200 / yr
Posted
21 days ago
Freshness
Confirmed live today
Closes
Apr 4, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $223k
This role $176k
$124k $294k
below market most similar roles pay here above market

This role pays less than 80% of similar roles. Most pay $191,500–$253,812 — the blue band above. At the midpoint, this role pays about $176k versus about $223k 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 Engineer, Machine Learning Engineering (ML Apps)

JOB TITLE: Sr Engineer, Machine Learning Engineering (ML Apps) The Sr Engineer, Machine Learning Engineering (ML Apps) joins the Machine Learning Engineering team to advance Generative AI technology for the edge. In this role, you will work within a multi-disciplinary research environment to architect, design, develop, test, and deploy on-device prototype software for cutting-edge AI use cases. Your daily work involves enabling on-device AI through modern software engineering best practices, including low-level system debugging, performance tuning, memory analysis, and native inference driver development. You will utilize expert-level C++, Python, and PyTorch to build solutions. The role requires deep knowledge of embedded software, neural network model optimization, and on-target deployment. You will specifically address technical challenges related to model quantization, hardware acceleration, and inference pipelines for mobile computing platforms and IoT devices.

What you'll do

  • Architect, design, and develop on-device prototype software for cutting-edge AI use cases.
  • Test and deploy AI models on mobile, laptop, autonomous vehicle, and IoT devices.
  • Perform low-level system debugging, performance tuning, and memory analysis.
  • Develop and debug native inference drivers for hardware acceleration.
  • Optimize neural network models for on-target deployment and edge inference.
  • Implement Generative AI technologies including LLMs and VLMs on mobile platforms.
  • Integrate native frameworks using Java, JNI, and the Android NDK.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of relevant work experience.
  • Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of relevant work experience.
  • PhD in Computer Science, Engineering, Information Systems, or related field.
  • At least 3 years of work experience in a relevant field.
  • Expert-level proficiency in C++ and Python with a strong foundation in software design, development, and optimization.
  • Knowledge of deep learning and ML frameworks such as PyTorch.
  • Hands-on experience in low-level system debugging, performance tuning, memory analysis, and native inference driver development.
  • Experience in Embedded Software development.
  • Experience with Android development, including Java, JNI, NDK, and native framework integration (preferred).
  • Knowledge of Generative AI technologies, including LLMs, VLMs, and inference pipelines (preferred).
  • Knowledge of neural network model optimization and on-target deployment (preferred).
  • Previous experience with Docker, Git, and CI/CD (preferred).
  • Knowledge of NPUs and ML accelerators (preferred).

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