Meta is seeking AI Research interns to join their Video Recommendations team within Facebook. The core mission of this team is to make all video formats (Reels, long videos, and Live streams) successful, as video consumption accounts for over 56% of time spent globally on the App and is expected to grow. The job involves optimizing the recommendation system to provide users with engaging and high-quality content, bridging business needs with foundational ML investments.
Requirements
- 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
- 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
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
Other
- 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
- 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
- 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
