Meta is seeking Research Interns to join Fundamental AI Research (FAIR) Multimodal Foundations teams. These teams are committed to advancing the field of Artificial Intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as Natural Language Processing, Audio and Speech processing, Computer Vision, Machine Learning, Deep Learning, and Reinforcement Learning. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our teams are looking for candidates to push the scientific and technical boundaries of multimodal generative AI. We are seeking individuals with expertise in generative modeling and computer vision, focusing on advanced topics like generative diffusion and transformer architectures, spatio-temporal modeling, multimodal dialogue and multimodal integration. Our team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.
Research Scientist Intern, FAIR - Generative Vision (PhD) Responsibilities
- Conduct research on advanced topics in video and image generation
- Brainstorm with research mentors, review literature and existing solutions of a challenging real-world research problem
- Develop novel solutions, implement prototypes, and perform extensive experiments for large-scale generative systems to test the proposed solutions in meaningful benchmarks and metrics, analyze the results and verify the conclusions
- Draft and polish research reports and/or publications
- Present research outcomes to internal and/or external audiences
- Contribute research that can be applied to Meta product development
Minimum Qualifications
- Currently has or is in the process of obtaining a PhD degree in the field of Computer Vision, Machine Learning, Artificial Intelligence, or equivalent
- Strong research background evidenced by publications at top conferences such as CVPR, NeurIPS, ICLR, ICCV, ICML or SIGGRAPH
- Solid understanding of generative models (diffusion models, GANs, VAEs, autoregressive transformers, etc.)
- Proficiency in deep learning frameworks such as PyTorch
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences in Speech & Language (ACL, EMNLP, NAACL, TACL, ICASSP, Interspeech, SLT, ASRU, TASLP)
- Experience advancing AI techniques in Natural Language Processing, including contributions to open source libraries and frameworks in Speech & Language
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences in Computer Vision (CVPR, ECCV, ICCV) or Machine Learning (NeurIPS, ICML, ICLR)
- Experience advancing AI techniques in Computer Vision and/or Machine Learning
- 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
- Experience working with large-scale datasets and compute infrastructure
- A strong track record of contributions to open-source projects, benchmarks, or shared research artifacts
- Intent to return to degree-program after the completion of the internship/co-op
