Research Scientist Intern, Video Recommendations (PhD)

Meta•Menlo Park, CA

5d•$7,650 - $12,667

About The Position

Meta is seeking a PhD-level AI Research intern for its Facebook Video Recommendations team. The team recommends video content—including Reels, long videos, and Live streams—and works to make these formats successful on Facebook. The intern will primarily work with Facebook video content and optimize recommendation systems to provide users with engaging, high-quality content. The intern will help frame practical, high-impact recommendation challenges as rigorous machine-learning problems and develop innovative solutions with guidance from Research Scientists and Software Engineers. The work focuses on end-to-end challenges at the intersection of product, machine learning, and infrastructure, connecting business needs with longer-term foundational investments through machine-learning approaches. Internships last 12 to 24 weeks, with various start dates throughout the year.

Requirements

Currently have or be in the process of obtaining a Ph.D. in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or a relevant technical field.
Obtain work authorization in the country of employment by the time of hire and maintain work authorization during employment.
Have experience with Python, C++, C, Java, or another related programming language.
Have experience with deep-learning frameworks such as PyTorch or TensorFlow.
Be familiar with machine learning and common deep-learning architectures.

Nice To Haves

Intent to return to the degree program after completing the internship or co-op.
A record of research achievements demonstrated through grants, fellowships, patents, or publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, or KDD.
Research or project experience in one or more of reinforcement learning, pre-training and supervised fine-tuning of large language models, sequence modeling, diffusion models, and their applications in recommendation systems.
Software development experience through technical internships, work experience, coding competitions, or widely used contributions to open-source machine-learning repositories.
Experience working and communicating cross-functionally in a fast-paced team environment, with the ability to identify research opportunities in real-world applications, select appropriate machine-learning methods, and drive iterations based on analysis of results.

Responsibilities

Perform research to advance the science and technology of intelligent machines.
Develop novel and accurate NLP algorithms and systems using deep learning and machine learning on large-scale data resources.
Analyze and improve the efficiency, scalability, and stability of deployed systems.
Collaborate with researchers and cross-functional partners, communicating research plans, progress, and results.
Publish research results and contribute to research applicable to Meta product development.