Qualcomm AI Research is seeking an outstanding Applied Research Scientist with deep expertise in Large Language Models (LLMs) and Vision-Language Models (VLMs). This role focuses on advancing generative AI technologies and optimizing foundation models for deployment on resource-constrained devices. You will lead cutting-edge research on model architectures, training strategies, and efficiency techniques to enable next-generation AI experiences.

What You’ll Do

Design and train state-of-the-art foundation models for multi-modal applications.
Develop algorithms for efficient inference and model compression to meet on-device constraints.
Collaborate across hardware, software, and systems teams to bring research innovations to life on next-generation devices.
Your work will directly impact smartphones, autonomous vehicles, robotics, and IoT systems worldwide.

Key Responsibilities

Foundation Model Fine-Tuning: Lead fine-tuning of large-scale LLMs and VLMs for multi-modal and agentic tasks.
System Prototyping: Build and validate agentic AI prototypes for on-device and cloud deployment.
Model Efficiency: Innovate quantization, pruning, and distillation strategies without sacrificing accuracy.
Programming & Experimentation: Implement solutions in Python and PyTorch; manage large-scale experiments and benchmarks.

Mentoring & Training: Provide guidance and mentorship to junior engineers and ERP residents, fostering technical growth and professional development.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Minimum Qualifications

Ph.D. in Computer Science, Machine Learning, or related field (or equivalent experience).
Proven experience in training large-scale LLMs/VLMs or foundation models.
Strong background in deep learning, generative AI, and multi-modal architectures.
Proficiency in Python and PyTorch; experience with distributed training frameworks.

Preferred Qualifications

3+ years of hands-on experience in developing and optimizing foundation models.
Strong expertise in quantization, pruning, and techniques for efficient inference.
Familiarity with hardware-aware AI optimization and deploying models on edge devices.
Track record of publications in leading ML/AI conferences (e.g., NeurIPS, ICML, CVPR, ACL).

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 disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able 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 confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

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

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