Research Scientist Intern, Video Recommendations (PhD)
Bellevue, WA | Menlo Park, CA
Meta is seeking AI Research interns to join our Video Recommendations team within Facebook. Videos (Reels, long videos, and Live streams) are increasingly the formats of choice across the social media industry, and making all these formats successful is a top priority for Facebook, and the core mission owned by this org. Time spent on Facebook watching videos accounts for 1.2+ Billion hours/day, which is over 56% of time spent globally on the App, and this number is expected to continue growing.
This team is directly in charge of recommending all sorts of videos to users. In this role, you'll be working primarily with Facebook's video content, which is predominantly driven by our recommendation system. Your job will involve optimizing our system to provide users with the most engaging and high-quality content. Our interns will have the opportunity to participate in the process of framing practical, high-impact challenges in recommendation into rigorous machine learning problems, and bring their own expertise to build innovative solutions under the guidance from our Research Scientists and Software Engineers.
More concretely, you will focus on solving end-to-end problems in the intersection of Product, ML and Infra, and serve as a bridge between high-demand business needs and long-term foundational investments via ML approach.
Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, Video Recommendations (PhD) Responsibilities
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
This team is directly in charge of recommending all sorts of videos to users. In this role, you'll be working primarily with Facebook's video content, which is predominantly driven by our recommendation system. Your job will involve optimizing our system to provide users with the most engaging and high-quality content. Our interns will have the opportunity to participate in the process of framing practical, high-impact challenges in recommendation into rigorous machine learning problems, and bring their own expertise to build innovative solutions under the guidance from our Research Scientists and Software Engineers.
More concretely, you will focus on solving end-to-end problems in the intersection of Product, ML and Infra, and serve as a bridge between high-demand business needs and long-term foundational investments via ML approach.
Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, Video Recommendations (PhD) Responsibilities
- Initiate and lead efforts towards ambitious research goals, while identifying intermediate milestones to reach and gathering insights step by step.
- Conduct innovative research on deep-learning algorithms and models that can eventually be deployed into Meta’s recommendation products, meeting industry-level requirements on efficiency, scalability, and stability.
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results. Document findings and share learnings internally.
- Publish research results and contribute to research that can be applied to Meta product development.
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science or a related field.
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- Familiarity with machine learning and common deep learning architectures.
- Experience with Python, especially machine learning libraries such as Pytorch and TensorFlow.
- Intent to return to degree-program after the completion of the internship/co-op.
- Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as NeurIPS, ICML, ICLR, KDD, ACL, EMNLP, etc.
- Past experience in conducting research on recommendation system, graph representation learning.
- Demonstrated software development experience via tech internships, work experience, coding competitions, or widely used contributions in open source machine-learning repositories.
- Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results.
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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Categories:
Data Science Jobs
Research Jobs
Tags: Architecture Computer Science Deep Learning EMNLP ICLR ICML Machine Learning NeurIPS Open Source PhD Physics Python PyTorch Research TensorFlow VR
Perks/benefits: Career development Conferences Equity / stock options Health care Salary bonus
Region:
North America
Country:
United States
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