Research Scientist Intern - Content Seal - FAIR

MetaParis, Île-de-FranceOn-siteInternshipListed 2 days ago

Apply now

About this role

Meta is looking for Research Interns to join our Fundamental AI Research (FAIR) organization, within Meta Superintelligence Labs. The role of FAIR is to drive long-term research for Meta. We publish groundbreaking papers and release frameworks/libraries that are widely used in the open-source community. We closely collaborate with other organizations at Meta to bring the latest research findings to production.

The team where this role sits is exploring new approaches to making AI safer, fighting deepfakes and preventing harmful content. Past work in that space includes watermarking models such as TextSeal, AudioSeal, or VideoSeal, and downstream extensions such as data traceability and benchmark leakage detection. The mission is to develop state-of-the-art algorithms that can protect our users across our platforms, with a focus on open research and scientific novelty.

This is a 2026 internship opportunity with start dates from May to September. To learn more about our research, visit https://research.facebook.com.

Responsibilities

Perform research to advance the science and technology of intelligent systems.
Develop novel, accurate and efficient multimodal generative models for text, image, and other media.
Contribute research that can be applied to Meta products.
Analyze and improve efficiency, scalability, and stability of various deployed systems.

Qualifications

Currently has, or is in the process of obtaining a MS or Ph.D. degree in AI or a related field
Experience in PyTorch, Python or C/C++
Experience training generative models for text, audio, image or video
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Intent to return to degree-program after the completion of the internship/co-op
Comfortable manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ACL, EMNLP, NAACL, AAAI, ICML, NeurIPS, ICLR, Interspeech, ICASSP, ICCV, CVPR
Ability to communicate complex research in a clear, precise, and actionable manner
A strong interest in theoretical and empirical research and for answering hard questions with research
Interpersonal experience: cross-group and cross-culture collaboration