Artificial Intelligence for Video Compression - Research Scientist

Company:Qualcomm Technologies, Inc.Job Area:Engineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:Qualcomm's Multimedia R&D and Standards Group is seeking a candidate for the position of Video Compression Research Engineer with a focus on machine learning for video compression. You join a world-renowned team of video compression experts who develop algorithms, hardware architectures, and systems for state-of-the-art applications of classical and machine learning methods in video compression, video processing, point cloud coding and processing, AR/VR and computer vision use cases. The ideal candidate will be a highly self-directed individual with strong creative and analytic skills, and a passion for machine learning and video compression technologies. This role offers the opportunity to contribute to groundbreaking advancements in video compression technology and working with a team of experts in a dynamic and collaborative environment.We are considering candidates with various levels of experience. We are flexible on location and open to hiring anywhere, with preferred locations in USA, Germany and Taiwan.Responsibilities:Contribute to the conception, development, implementation, and optimization of new Neural Networks based algorithms allowing improved video compression.Represent Qualcomm in the related standardization forums: JVET, MPEG Video, and ITU-T/VCEG.Document and present new algorithms and implementations in various forms, including standards contributions, patent applications, conference papers and presentations, and journal publications, etc.Ideal candidate would have the skills/experience below:Developed innovative artificial intelligence/machine learning algorithms preferably related to data compression or computer vision.Knowledge of the theory, algorithms, and techniques used in video and image coding.Experience in video compression standards, such as VVC/H.266 or HEVC/H.265, is a significant benefit.Track record of successful research accomplishments demonstrated through published papers at leading conferences, and/or patent applications.Excellent programming skills including Python and C/C++ combined with knowledge of at least one machine learning framework such as PyTorch.Strong written and verbal English communication skills, great work ethic, and ability to work in a team environment to accomplish common goals.Qualifications:PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics, or similar fields.1+ years of experience with programming language such as C, C++, MATLAB, etc.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. ORMaster'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. ORPhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.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 [email protected] 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).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 and Other Compensation & Benefits: $158,400.00 - $237,600.00The 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 – and you can review more details about our US benefits at this link.If you would like more information about this role, please contact Qualcomm Careers.Job Posting Date:2025-09-26Job Posting End Date:Additional Job Posting Location:Hsinchu City TWN; Munich DEUDepartment:Machine Learning Engineering