Research Scientist (l5) - Content Understanding

Netflix Netflix · Big Tech · United States · Remote · Data & Insights

Research Scientist at Netflix focused on content understanding and merchandising. The role involves designing and developing models, conducting quality evaluations for algorithms, and applying ML/Gen AI to video, audio, and textual data. The goal is to improve content metadata and the discovery experience for members.

What you'd actually do

  1. Collaborate closely with stakeholders in Product Discovery & Promotion to learn deeply about content metadata and merchandising and identify potentially impactful problems to solve via scalable machine learning and artificial intelligence solutions
  2. Develop innovative systems and models that empower decision-making for stakeholders and product features that can deliver member joy by leveraging a wide variety of metadata and production media generated by and collected from our productions throughout their end-to-end lifecycle
  3. Collaborate with team members and cross-functional partners to operationalize your models so that they can be integrated seamlessly into operational workflows
  4. Serve as a key thought partner for stakeholders, cross-functional partners, and our diverse set of team members regarding machine learning algorithms and system architectures

Skills

Required

  • Ph.D. or MS degree in a quantitative or computational field
  • 4+ years of full-time work experience in one or more relevant machine-learning roles
  • Practical experience in supervised, unsupervised, and deep machine learning methods
  • Practical experience applying machine learning and Gen AI solutions to video, audio, and/or textual data sources
  • Practical experience operationalizing or productionizing machine learning and/or artificial intelligence solutions
  • Exceptional written and oral communication with technical and non-technical audiences

Nice to have

  • developing quality evaluations via mechanisms such as LLM-as-a-judge or LLM juries
  • Comfortable and effective in ambiguous problem spaces; ability to own and drive projects with minimal oversight and process

What the JD emphasized

  • Ph.D. or MS degree in a quantitative or computational field
  • 4+ years of full-time work experience in one or more relevant machine-learning roles
  • Practical experience in supervised, unsupervised, and deep machine learning methods
  • Practical experience applying machine learning and Gen AI solutions to video, audio, and/or textual data sources
  • developing quality evaluations via mechanisms such as LLM-as-a-judge or LLM juries
  • Practical experience operationalizing or productionizing machine learning and/or artificial intelligence solutions
  • Comfortable and effective in ambiguous problem spaces; ability to own and drive projects with minimal oversight and process

Other signals

  • develop models
  • develop quality evaluations
  • machine learning and artificial intelligence solutions
  • operationalize your models