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Deep Learning Model Efficiency Research Engineer

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Qualcomm
Full Time position
Listed on 2026-01-12
Job specializations:
  • Engineering
    AI Engineer, Software Engineer, Computer Science
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Computer Science
Job Description & How to Apply Below

Company:

Qualcomm Korea YH

Job Area:

Engineering Group, Engineering Group >
Machine Learning Engineering

General

Summary:

Qualcomm AI Research is looking for world‑class researchers and engineers in machine learning and deep learning. Come join a high‑caliber team of engineers building advanced machine learning technology, on‑device AI solutions, and user‑friendly model optimization tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit () to enable state‑of‑the‑art networks to run on devices with limited power, memory, and computation. We are looking for talented researchers and engineers with experience in machine learning to enable embedded deep learning.

We solve challenging problems to improve speed, accuracy, and power‑consumption of deep neural networks. Your responsibility will be to apply our model‑efficiency tools on a wide variety of use cases, provide detailed analysis, optimize algorithms, develop best practices, and contribute to the continuous evolution of model‑efficiency tools.

Required Skills:
  • Bachelor’s degree in Engineering, Computer Science, or related field.
  • Strong understanding of Machine Learning fundamentals and strong programming skills with ML frameworks.
  • Excellent analytical, development, and debugging skills.
  • Excellent interpersonal, written and oral communication skills.
Preferred

Skills:
  • MS or PhD in Computer Science/Engineering with 1+ years of professional experience or equivalent experience.
  • 2+ years of proven experience in algorithm design and software development for machine learning; proficiency in designing, implementing and training DL/RL algorithms in high‑level languages/frameworks (PyTorch and Tensor Flow).
  • Strong background in at least one of the following fields:
    Machine learning theory/optimization methods;
    Model compression/quantization/optimization for embedded devices;
    Neural Architecture Search/kernel optimization;
    Computer vision;
    Audio and speech/NLP.
  • Experience with improving efficiency of AI algorithms for deployment, including familiarity with open‑source solutions such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit ().
Minimum Qualifications:
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field AND 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • Master’s degree in Computer Science, Engineering, Information Systems, or related field AND 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • PhD in Computer Science, Engineering, Information Systems, or related field.
Applicants:

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e‑mail disabili or call Qualcomm's toll‑free number. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able to participate in the hiring process.

Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of company confidential information and other proprietary information, to the extent those requirements are permissible under applicable law.

If you would like more information about this role, please contact Qualcomm Careers.

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