AI Researcher, On-Device LLM Efficiency

Qualcomm; San Diego (CA); On-site; USD 138,800 - 208,200; Full time

Benefits offered by this job

Competitive discretionary bonus

Annual RSU grants

Benefits package

Job summary

Qualcomm Technologies, Inc. seeks a Machine Learning Researcher to conduct fundamental ML research that pushes beyond state-of-the-art performance. You will collaborate with cross-functional teams to advance ML methods for mobile, edge, auto, and IoT products.

The role emphasizes on-device AI deployment, efficient attention, and inference acceleration, with opportunities for publishing in top AI conferences and contributing to RSU programs.

Qualifications

• Master's degree in Computer Science, Electrical Engineering, or related field.
• 4+ years AI research experience.
• Strong background in deep learning and Transformers.
• Proficiency with Python and PyTorch.
• Experience in LLM reasoning or inference acceleration research.

Responsibilities

• Research and development in LLM inference efficiency algorithms, efficient model architecture design, and/or LLM training.
• Develop creative solutions with consideration of practical challenges on devices.
• Implementation and evaluation of possible solutions in both simulation and on-device environments.

Skills

Python

PyTorch

Transformers

LLM reasoning

Inference acceleration

Education

Master's degree in Computer Science

Master's degree in Electrical Engineering

PhD preferred

Tools

Python

PyTorch

Job description

Company

Qualcomm Technologies, Inc.

Job Area

Engineering Group / Machine Learning Researcher

General Summary

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Researcher, you will conduct fundamental research that creates innovative machine learning methodology achieving beyond state-of-the-art performance. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IoT products through machine learning research.

Responsibilities

• Research and development in the area of LLM inference efficiency algorithms, efficient model architecture design, and/or LLM training.
• Develop creative solutions with consideration of practical challenges on devices.
• Implementation and evaluation of possible solutions in both simulation and on-device environments.

Minimum Qualifications

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
• 6+ months of academic and/or work experience developing and/or optimizing machine learning models, systems, platforms, or methods.

Qualifications

• Master's degree in Computer Science, Electrical Engineering, or related field.
• 4+ years of AI research experience.
• Strong background in deep learning and Transformers.
• Strong programming skills in Python and PyTorch.
• Experience in LLM reasoning or inference acceleration research.

Preferred Qualifications

• PhD in Computer Science, Electrical Engineering, or related field.
• Experience in LLM efficiency research such as efficient attention, inference acceleration, or KV cache compression.
• Experience in on-device AI deployment on mobile or edge devices.
• Publishing research papers at top-tier AI/ML conferences, e.g., NeurIPS, ICML, and ICLR, as a lead author.

Equal Opportunity & EEO Statement

Qualcomm is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification. Qualcomm is committed to providing an accessible process for individuals with disabilities and will provide reasonable accommodations to support them in the hiring process.

Compensation & Benefits

$138,800.00 - $208,200.00. Additional benefits include a competitive annual discretionary bonus program, opportunity for annual RSU grants, and a highly competitive benefits package to support success at work, at home, and at play.

Contact

For more information about this role, please contact Qualcomm Careers.