Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Researcher

General Summary:

Qualcomm's Multimedia R&D and Standards Group is seeking passionate candidates with expertise in Computer Vision and Computer Graphics. The team is developing advanced AI and deep learning algorithms, architectures, and systems for applications enriching the embedded systems for Smartphone and Extended Reality.

The candidate should bring a deep understanding in computer vision or computer graphics, exhibiting excellent analytical and algorithm development skills and proficiency in Python and C/C++ programming. The selected candidate will have responsibilities in the following areas:

• Research and develop efficient deep learning architectures and models for AI-enabled camera and extended reality. This includes but not limited to generative text-to-video model, face analytics, gaze estimation, facial micro-expression recognition/synthesis, face and body synthesis, and 3D body/face reconstruction from 2D images.

Must have Qualifications

• Master's or PhD degree in Electrical Engineering, Computer Science, and/or closely related field.

• 3+ years of professional experience in computer deep learning software development for applications like Computer Vision or Computer Graphics.

• 5+ years of experience developing practical deep learning algorithms using PyTorch, TensorFlow, or other deep learning frameworks.

• Solid Background in Computer Vision or Computer Graphics.

• Solid background in machine/deep learning fundamental knowledges and mathematics.

• Academic publications in computer vision research at top conferences and journals (PAMI, IJCV, NeurIPS, CVPR, ICCV, ICLR, ICML, etc.)

• Proficiency in C/C++ and Python programming.

Preferred Qualifications

• Education: Ph.D. - Computer Science or Electrical Engineering

• Excellent knowledge of C++ and object-oriented programming, capability to design and implement robust, high-performance, and flexible system software.

• Expertise in various networks architectures such as diffusion, transformer, Gaussian Splatting, NeRF, StyleGan, U-Nets, ResNets models.

• Experience in deep learning based high resolution face editing

• Experience in micro-expression recognition and synthesis

• Experience in ego-centric computer vision

• Experience of deep learning model pruning, compression, and quantization for executing on edge device without performance decreasing.

• Excellent written and verbal communication skills.

• Track record of driving ideas from design through commercialization.

• Experience in computer vision algorithm design development and integrating machine learning algorithm into camera systems.

• Self-motivated and strong desire to learn new technologies, design novel techniques and propose them for technology commercialization.

• Team Player.

Minimum Qualifications:

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

PhD 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.

Although this role has some expected minor physical activity, this should not deter otherwise qualified applicants from applying. If you are an individual with a physical or mental disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here (https://qualcomm.service-now.com/hrpublic?id=hr_public_article_view&sysparm_article=KB0039028) for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities as part of our ongoing efforts to create an accessible workplace.

Qualcomm is an equal opportunity employer and supports workforce diversity.

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.

EEO Employer: 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 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.

Pay range:

$150,500.00 - $225,500.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer!

If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) .

EEO Employer: 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