Research Scientist Intern, Video Recommendations (PhD)

Meta; Bellevue (WA); On-site; USD 69,000 - 96,000; Full time

Job summary

Meta in Bellevue, WA seeks an AI Research Intern to join the Video Recommendations team. You will tackle end-to-end ML problems at the intersection of product, ML, and infra, focusing on video content recommendation and NLP techniques.

The role offers exposure to state-of-the-art models, collaboration with researchers and engineers, and opportunities to publish and contribute to practical Meta products. Internships run 12–24 weeks with multiple start dates.

Qualifications

• Currently enrolled in or pursuing a Ph.D. in Computer Science, AI, NLP, or related field.
• Proven track record of research with publications or equivalent.
• Demonstrated ability to work with ML and DL frameworks.

Responsibilities

• Perform research to advance AI and ML methods for video recommendation.
• Develop NLP algorithms and systems using DL on large data resources.
• Analyze and improve efficiency, scalability, and stability of deployed systems.
• Collaborate with researchers and cross-functional partners; communicate plans and results.
• Publish research findings applicable to Meta product development.

Education

PhD in Computer Science or related field

Tools

Python

C++

C

Java

PyTorch

TensorFlow

Job description

About

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 twenty-four (24) weeks long and we have various start dates throughout the year.

Responsibilities

• Perform research to advance the science and technology of intelligent machines
• Develop novel and accurate NLP algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources
• Analyze and improve efficiency, scalability, and stability of various deployed systems
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
• Publish research results and contribute to research that can be applied to Meta product development

Minimum Qualifications

• Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or relevant technical field
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
• Experience with Python, C++, C, Java or other related language
• Experience with deep learning frameworks such as Pytorch or Tensorflow
• Familiarity with machine learning and common deep learning architectures Intent to return to the 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, ACL, EMNLP and KDD
• Prior research or project experience in one or more of the following areas: reinforcement learning, pre-training and supervised fine-tuning of large language models, sequence modeling, diffusion models, and their applications in recommendation systems
• 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