Research Scientist Intern, AI Research - Multimodal Pretraining (PhD)

Beschreibung:

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization. Meta is seeking Research Scientist Interns in the multimodal pretraining team in the Meta Superintelligence org. We are committed to advancing the field of generative AI by making fundamental advances in technologies to help interact with and understand our world. We're looking for candidates who want to push the frontiers of multimodal pretraining, and have experience in developing novel language modeling architectures, vision-language modeling, multimodal generation, and neural scaling laws. Our team offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.
Perform research to advance the frontiers of multimodal (images, video, text, audio, and other modalities) pretraining, to develop the next generation of multimodal architectures. 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

Ihr Profil:

Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Machine Learning, Computer Vision, Artificial Intelligence, or relevant technical field Past projects/publications in the general domain of neural scaling laws, model architectures, image/text modeling, vision-language modeling Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Experience in PyTorch, Triton, or other related programming languages Experience building systems based on machine learning and/or deep learning methods Intent to return to a degree-program after the completion of the internship/co-op Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, and ACL Experience with Generative AI, including transformers, diffusion models and VLMs Background in advancing AI techniques at the intersection of foundation model training including core contributions to open source libraries and frameworks Publications or experience in machine learning, AI, computer vision, NLP, optimization, computer science, statistics, applied mathematics, or data science Experience solving analytical problems using quantitative approaches Experience setting up ML experiments and analyzing their results Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources Experience in utilizing theoretical and empirical research to solve problems Experience working and communicating cross functionally in a team environment