Scientist in Video Quality Optimization
2 weeks ago
About Netflix:
Netflix stands as a premier global entertainment platform, boasting 278 million paid subscribers across more than 190 nations. Our members enjoy a diverse array of TV shows, films, and games in various genres and languages, with the flexibility to watch at their convenience, pause, and resume as they wish.
The Opportunity:
The Challenge:
At Netflix, we are dedicated to providing our members with an unparalleled viewing experience. Our mission is to enhance streaming playback quality, whether it's enjoying a nature documentary on a state-of-the-art 4K HDR television or streaming a live event on the go. Additionally, we are venturing into cloud gaming, focusing on optimizing the quality of gameplay experience. We seek a Research Scientist in Video Quality to tackle these multifaceted challenges and lead innovative research in this domain.
Key Responsibilities:
- Drive research initiatives on advanced video quality metrics and partner with academic institutions.
- Execute subjective studies to analyze various factors influencing video quality, including HDR content and film grain.
- Create algorithm prototypes for objective video quality evaluation and rigorously assess their effectiveness across multiple benchmarks.
- Collaborate with software engineers and fellow scientists to translate research breakthroughs into practical applications.
- Comprehend the significance of video quality within the Netflix streaming framework and work alongside cross-functional teams to enhance member quality of experience (QoE) and overall Netflix value.
You are a motivated Research Scientist who excels in a dynamic setting. You proactively identify team needs and work effectively with diverse teams. Your research expertise is complemented by a solid foundation in human visual perception and signal processing. You are committed to personal and team improvement and are eager to make a significant impact on millions of Netflix members worldwide.
Essential Qualifications:
- 3+ years of research experience in perceptual video quality, with a proven record of achievements (e.g., publications, standardization, or algorithm productization).
- Master's degree in Electrical Engineering, Computer Science, or a related field; PhD preferred.
- Proficient in Python and object-oriented programming.
- Strong background in image and video processing, human visual perception, subjective testing methodologies, and objective quality metrics such as SSIM and VMAF.
- Experience in conducting subjective experiments and/or developing perceptual quality metrics.
- Familiarity with video compression techniques and adaptive streaming methodologies.
- Experience with multimedia frameworks like FFmpeg.
- Knowledge of machine learning applications in video quality assessment.
- Experience with crowdsourcing methods and large-scale subjective testing.
Our compensation model is straightforward, consisting solely of an annual salary, without bonuses. Each year, you have the flexibility to choose how much of your compensation is allocated to salary versus stock options. We determine your competitive compensation based on market indicators, your specific job family, background, skills, and experience. The salary range for this position is $170,000 - $720,000.
Netflix offers a comprehensive benefits package, including health plans, mental health support, a 401(k) retirement plan with employer matching, stock options, disability programs, health savings and flexible spending accounts, family-forming benefits, and life and serious injury benefits. Additionally, we provide paid leave programs, with full-time hourly employees accruing 35 days annually for vacation, holidays, and sick leave, while full-time salaried employees enjoy immediate access to flexible time off.
At Netflix, we foster a unique culture and environment. We are committed to being an equal-opportunity employer and celebrate diversity, recognizing that a variety of perspectives and backgrounds strengthens our teams. We take diversity and inclusion seriously and do not discriminate based on race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
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