Machine Learning Engineer, Staff (Model Optimization)

Qualcomm

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$162,000–$243,000 / yr
Posted
40 days ago
Freshness
Confirmed live yesterday
Closes
Mar 16, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $232k
This role $202k
$147k $300k
below market most similar roles pay here above market

This role pays less than 78% of similar roles. Most pay $208,375–$254,750 — the blue band above. At the midpoint, this role pays about $202k versus about $232k 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 · Machine Learning Engineer, Staff (Model Optimization)

The Machine Learning Engineer, Staff (Model Optimization) joins the Machine Learning Engineering group to create and implement techniques, frameworks, and tools for efficient machine learning discovery and utilization. This role involves modeling, architecting, and developing advanced machine learning hardware co-designed with software for inference or training solutions. You will develop optimized software, including machine learning kernels, compiler tools, and model efficiency tools to enable AI models on hardware. Key responsibilities include overseeing experiments to train and evaluate models and prototyping novel solutions for complex products. Required skills include proficiency in frameworks like TensorFlow, Caffe, Keras, and PyTorch, along with programming languages such as Python, C, and C++. You will also utilize statistics, probability, and low-level interactions between operating systems like Linux and Android.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

See salary data

What you'll do

  • Extend training or runtime frameworks and model efficiency software tools with new features and optimizations.
  • Model, architect, and develop advanced machine learning hardware co-designed with software for inference or training.
  • Develop optimized software including machine learning kernels and compiler tools to enable AI models on hardware.
  • Apply machine learning techniques into products and AI solutions to enable customer-facing features.
  • Prototype novel machine learning solutions aligned with product roadmaps and complex feature requirements.
  • Oversee and conduct experiments to train and evaluate machine learning models and software.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of relevant engineering experience.
  • Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of relevant engineering experience.
  • PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of relevant engineering experience.
  • Master's degree in Computer Science, Engineering, Information Systems, or related field (preferred).
  • 5+ years of experience with Machine Learning frameworks such as TensorFlow, Caffe, PyTorch, or Keras (preferred).
  • 5+ years of experience in embedded system development and optimization for ML domains like NLP or multi-media (preferred).
  • 5+ years of experience with programming languages suitable for machine learning such as Python, R, C, or C++ (preferred).
  • 5+ years of experience using statistics and probability, including conditional probability and Bayes rule (preferred).

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