Qualcomm Jobs

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

The volume of video data is experiencing exponential year-on-year growth. Consequently, the cost of transmitting and storing video is rapidly becoming prohibitive for service providers, such as cloud and streaming platforms. These challenges increasingly necessitate the improvement of existing high-performance video codecs. For this purpose, Qualcomm's Multimedia R&D Standards Group is seeking a machine learning research scientist to help develop the next generation of AI-enabled video codecs, leveraging recent advancements in generative AI. You will be part of world-class team of renowned data compression experts that have successfully developed many of the algorithms and systems video platforms use today. The candidate should be self-directed, highly motivated and demonstrate a passion for generative vision models, along with their deployment to the edge (e.g. on Qualcomm‘s NPU). You will work on, but not be limited to, developing novel applications of AI methods in video compression. Experience of video coding is desired, but not a requirement.

We are considering candidates with various levels of experience. We are flexible on location and open to hiring anywhere, preferred locations are USA and Germany.

Responsibilities:

• Contribute to the conception and implementation of new algorithms for improved video compression.

• Initiate ideas, design and implement algorithms for computationally lightweight model architectures.

• Represent Qualcomm in 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 and journal publications, presentations, etc.

Ideal candidate would have the skills/experience below:

• Prior expertise in one or more aspects of generative models of video data (e.g., optical flow, implicit neural representations, video or single-image super-resolution, diffusion models, density estimation, transformers, etc.)

• Track record of impactful work at major conferences in machine learning or computer vision (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, etc.).

• Highly proficient Python programming skills, and familiarity with PyTorch.

• Strong written and verbal English communication skills, great work ethic, and ability to work in a high-performing environment.

• PhD or Master’s degree in Machine Learning, Computer Vision, Physics, Mathematics, Electrical engineering or similar field, or equivalent practical experience.

• Some knowledge of video compression algorithms, such as ECM, VVC, HEVC, H.264, and AV1.

Qualifications:

• PhD or Masters degree in Machine Learning, Computer Vision, Physics, Mathematics, Electrical engineering or similar field, or equivalent practical experience. · 3+ years of experience in machine learning and AI, either in an academic or industry research lab.

• Track record of impactful work at major conferences in machine learning or computer vision (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, 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.

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.

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.

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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:

$148,500.00 - $222,500.00

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