N
Netflix
N
Netflix
Posted 2 months ago
Internship
Los Gatos, California
In Person
Smart Summary
Responsibilities
The intern will investigate Gaussian Splatting as a future streaming format by developing compression strategies and optimizing training times. They will design and implement a proof-of-concept system to demonstrate GS-based rendering on relevant content.
Qualifications
You are currently pursuing a PhD in a technical field with an expected graduation date in June 2027 or later. You have a strong track record in research related to 3D/4D scene reconstruction, novel-view synthesis, or 3D computer vision, along with solid machine learning and deep learning expertise.
Must Have Skills for ATS
Gaussian Splatting
Python
3D scene reconstruction
novel-view synthesis
NeRF
differentiable rendering
neural graphics
3D computer vision
machine learning
deep learning
CUDA
WebGL
video compression
HEVC
AV1
Job Description
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
The Role
Gaussian Splatting (GS) is a 3D/4D scene reconstruction technique that enables photorealistic novel-view synthesis with low rendering complexity, making it attractive for deployment on consumer devices such as TVs, streaming sticks, phones, and laptops. Realizing this vision requires addressing several open technical challenges, such as a significant reduction in model training/encoding time and more efficient compression. As part of the Video Algorithms team during this 24-week Fall internship, you will help us investigate the potential of GS as a future streaming format and explore possible improvements, with a focus on building towards a practical system.
During the internship, you will:
Explore GS model compression strategies using open datasets
Contribute to early thinking on additional dataset needs for representative scenes.
Characterize trade-offs among GS model size, training time, and rendered quality, and quantify the gap relative to streaming-rate targets
Identify and experiment with strategies to reduce training/encoding time and/or to improve GS compression efficiency
Design and implement a proof-of-concept (PoC) that showcases GS-based rendering on content of interest
Who Are You?
Currently pursuing a PhD in a technical field such as Computer Science, Engineering, Math, or Statistics, with an expected graduation date in June 2027 or later.
Thrives working in complex, dynamic, and fast-moving environments.
Strong software development skills and feels comfortable with software engineering best practices (e.g., version control, testing, code review, etc.).
Successful track record in research of 3D/4D scene reconstruction, novel-view synthesis, Gaussian Splatting or NeRF, differentiable rendering, neural graphics, or 3D computer vision.
Solid understanding of machine learning and deep learning concepts, with hands-on experience training and evaluating ML models.
Able to program fluently in Python
Nice to Have:
Familiarity with real-time rendering and GPU programming (CUDA, WebGL, graphics pipelines).
Background in video compression, streaming systems, or codec standards such as HEVC and AV1.
Involvement in open-source multimedia or graphics projects.
Experience with large-scale distributed systems and cloud computing.
To learn more about our team, check out some of our tech blogs:
https://netflixtechblog.com/av1-now-powering-30-of-netflix-streaming-02f592242d80
https://netflixtechblog.com/av1-scale-film-grain-synthesis-the-awakening-ee09cfdff40b
https://netflixtechblog.com/toward-a-practical-perceptual-video-quality-metric-653f208b9652
https://netflixtechblog.com/per-title-encode-optimization-7e99442b62a2
Internships at Netflix
At Netflix, we offer a personalized experience for interns, and our aim is to mimic what it is like to actually work here. We match qualified interns with projects and groups based on interests and skill sets, and fully embed interns within those groups for the summer. Netflix is a unique place to work and we live by our values, so it's worth learning more about our culture.
Internships are paid and are a minimum of 12 weeks,. Conditions permitting, our summer internships will be located in our Los Gatos, CA office, or in our Los Angeles, CA office, depending on the team.
At Netflix, we carefully consider a wide range of compensation factors to determine the Intern top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
The overall market range for Netflix Internships is typically $40/hour - $110/hour.
This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here.
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
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