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The goal of our Content Management & Distribution Data Science and Engineering team is to enable operational and creative excellence in the distribution and promotion of our content on our service. We collaborate closely with our partners in the Product Discovery & Promotion organization, and our work directly contributes to launching high-quality content on our service and helps our members discover content they will love. We conduct analyses, build analytical tools, and develop models to help our partners execute on these primary objectives.
We are looking for a talented Research Scientist to join our Merchandising & Content Understanding pod, which focuses on deepening our content metadata across all formats and improving the discovery experience on our service. You will design and develop models and conduct quality evaluations for algorithms that will power the next generation of capabilities for our business. You will partner with our world-class team of creative production practitioners and various cross-functional teams to shape strategy and deliver impact via machine learning and artificial intelligence solutions. Interested? Read more about the job description and qualifications below!
What you will do:
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
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
Collaborate with team members and cross-functional partners to operationalize your models so that they can be integrated seamlessly into operational workflows
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
Your background and characteristics:
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, and 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
Exceptional written and oral communication with technical and non-technical audiences
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