Video Algorithms Intern

2 Months ago • Upto 1 Years • Research Development

Job Summary

Job Description

As a Video Algorithms Intern at Netflix, you'll develop machine-learning-based tools for next-generation video coding standards. This involves improving the tradeoff between compression efficiency and reconstruction quality using ML models alongside traditional signal processing. The internship will focus on investigating state-of-the-art ML architectures and training techniques for creating low-complexity models. You will work on projects aimed at reducing video data size for efficient transfer while maintaining high video quality. This is a 6-month internship requiring strong software development skills (Python, C/C++), expertise in video algorithms, and a solid understanding of machine learning concepts.
Must have:
  • PhD in technical field (CS, Engineering, Math, Statistics)
  • Strong software development skills (Python, C/C++)
  • Video Algorithms & Coding research experience
  • Solid ML/DL understanding & hands-on experience
  • Excellent communication skills
Good to have:
  • Understanding of video compression (HEVC, AV1)
  • Software performance optimization experience
  • Open-source multimedia project involvement
  • Large-scale distributed systems & cloud computing experience

Job Details

Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

Our Video Encoding organization has the big undertaking to run our production at scale and with high efficiency. As part of the Video Algorithm team during this 6-month internship, you will be actively developing machine-learning-based tools for next-generation video coding standards. Video encoding seeks to reduce the data size so that the files can be easily transferred between locations. However, it may introduce undesirable artifacts. Striking a good balance between compression efficiency and reconstruction quality is key. The use of ML models alongside traditional signal processing approaches can significantly improve this tradeoff by leveraging the rapidly growing computing powers from GPUs/NPUs. This internship project will investigate multiple state-of-the-art ML architectures as well as modern training techniques for distilling low-complexity models with this goal in mind. 

About You:

  • Currently pursuing a PhD in a technical field such as Computer Science, Engineering, Math, or Statistics, with a graduation date no earlier than Summer/Spring 2026 & continuous availability for the 6 month duration of the internship.

  • Thrives working in complex, dynamic, and fast-moving environments.

  • Articulate communicator across written and verbal communication mediums.

  • Strong software development skills and feel comfortable with software engineering best practices (e.g. version control, testing, code review, etc.).

  • Successful track record in Video Algorithms and Coding research or adjacent fields (Video Processing, Computer Vision, Video Quality).

  • Solid understanding of basic machine learning and deep learning concepts, hands-on experience with training and evaluating ML models.

  • Able to program fluently in Python and C/C++.

Bonus Points:

  • Solid understanding of video compression and processing, including codec standards such as HEVC and AV1.

  • Experience with software performance optimization on constrained hardware.

  • Involvement in open-source multimedia projects (ffmpeg, etc).

  • Experience with large-scale distributed systems and cloud computing.

To learn more about our team, check out the following article:

  •  

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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