Research Scientist Intern, Ads Recommendations (PhD)

Meta•Menlo Park, CA

1d•$7,650 - $12,667

About The Position

Meta is seeking Research Interns to join its Ads Recommendation team within Facebook. The team is responsible for recommending ads to users when they open the app. Interns will help frame practical, high-impact recommendation challenges as rigorous machine learning problems and develop solutions with guidance from research scientists and software engineers. The work addresses recommendation at large and rapidly changing content scales, with user preferences that can vary substantially across users and over time. Internships are 12 to 16 weeks, or 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 ongoing work authorization during employment.
Experience with Python, C++, C, Java, or another related programming language.
Experience with deep learning frameworks such as PyTorch or TensorFlow.
Experience building systems based on machine learning, deep learning methods, or natural language processing.
Familiarity with algorithms behind 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.
A record of 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 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.

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 big 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.