Research Scientist Intern, Feed Recommendations (PhD)

Meta•Bellevue, WA

20h•$7,650 - $12,667

About The Position

Meta is seeking Research Interns to join its Feed Recommendation team within Facebook. The team recommends content to users when they open the app and addresses practical challenges in recommendation at scale. Interns will help frame high-impact recommendation challenges as rigorous machine-learning problems and develop innovative solutions with guidance from research scientists and software engineers. The work involves generating relevant content sequences for a large and rapidly changing set of content and users whose preferences vary over time. Internships last 12 to 16 weeks, or 24 weeks, with various start dates throughout the year.

Requirements

Currently has or is pursuing a Ph.D. in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or a relevant technical field.
Must obtain work authorization in the country of employment by the time of hire and maintain authorization during employment.
Experience with Python, C++, C, Java, or another related language.
Experience with deep-learning frameworks such as PyTorch or TensorFlow.
Experience building systems based on machine-learning, deep-learning, or natural-language-processing methods.
Familiarity with algorithms for generative-model training and common deep-learning architectures, including Transformers, GPTs, and BERT.

Nice To Haves

Intent to return to the degree program after completing the internship or co-op.
Research achievements demonstrated by grants, fellowships, patents, or publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, and KDD.
Prior research or project experience in reinforcement learning, pre-training and supervised fine-tuning of large language models, sequence modeling, diffusion models, or 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 proactively 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, machine learning, and large 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.