Qualcomm
Artificial Intelligence for Video Compression - Research Scientist
$162K–$243K
San Diego, California · On-site · Full-time · Posted Oct 27, 2026
- Experience
- Minimum: Bachelor's degree and 4+ years, Master's degree and 3+ years, or PhD and 2+ years of relevant work experience. The posting also considers candidates with various levels of experience.
- Education
- Bachelor's, Master's, or PhD in a related field; qualifications also state a PhD or Master's degree in Electrical Engineering, Computer Science, Machine Learning, Applied Mathematics, or a related field.
About the job
Develop and optimize learning-based video compression algorithms, evaluate neural and hybrid compression systems, and contribute to video coding standards and research publications.
What you'll do
- Develop and optimize neural video coding, learned motion representation, and entropy modeling algorithms.
- Evaluate and improve compression systems using machine learning and rate-distortion optimization; contribute to relevant standards forums.
- Document and present research through standards contributions, patents, papers, presentations, and journals.
What they ask for
- Experience developing and evaluating machine learning models for compression, computer vision, or multimedia applications.
- Knowledge of video coding, rate-distortion optimization, and neural compression.
- Programming skills in Python and C/C++, and experience with PyTorch.
- Track record of research accomplishments through leading-conference publications and/or patent applications.
Nice to have
- Experience with learned image/video compression, computer vision, or generative AI.
- Experience with VVC/H.266, HEVC/H.265, AV1, or emerging neural video coding technologies.
Pay
$162,000.00 - $243,000.00 USD base salary
Tools
Python, C/C++, PyTorch, VVC/H.266, HEVC/H.265, AV1, JVET, MPEG Video
AI focus
Research and development of learning-based video compression, including neural video coding, learned motion representation, entropy modeling, and machine-learning-based compression evaluation and optimization.
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