Research Scientist Intern, FAIR - Video Generation (PhD)

Meta

Menlo Park, Seattle (CA, WA)

Presencial

USD 32.000 - 55.000

Jornada completa

Hace 3 días
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Descripción de la vacante

Meta is seeking Research Interns for the FAIR Communication & Language team within Meta Superintelligence Labs. Interns will work on video generation and post-training of large-scale models to advance perceptual and generative foundations for next-generation AI systems.

The team offers 12 to 24 week internships with various start dates. Candidates should be pursuing a PhD in a related field and have research experience in video generation or multimodal AI.

Formación

  • PhD candidate in CS/EE or related field with strong research track record.
  • Experience in video generation, computer vision, or multimodal AI.
  • Familiarity with large-scale model training and post-training optimization.

Responsabilidades

  • Contribute to development of video generation and multimodal models.
  • Experiment with post-training methods and data curation.
  • Collaborate with cross-functional teams and publish findings.

Conocimientos

Python
C++
PyTorch
Video generation
Multimodal AI
Research experience

Educación

PhD in Computer Science, Electrical Engineering, or related field

Herramientas

GitHub

Descripción del empleo

Meta is seeking Research Interns to join the Fundamental AI Research (FAIR) Communication & Language team within Meta Superintelligence Labs (MSL).

Our mission is to advance the science of intelligence and develop technologies that push the boundaries of AI. We are looking for interns with interest in video generation and post-training of large-scale models to help build the perceptual and generative foundations for next-generation AI systems. This internship offers the opportunity to collaborate with a highly interdisciplinary team of scientists, engineers, and cross-functional partners, leveraging cutting-edge technology, resources, and research facilities. Our interns have the opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.

We’re especially interested in candidates with expertise across video generation, computer vision, and multimodal AI, including:
  • Generative modeling for video (diffusion, flow matching, video synthesis)
  • Post-training of large-scale video and multimodal models (SFT/RL, optimization, data curation)
  • Video-language models and architectures for video generation
  • Multimodal understanding, reasoning, and generation
  • Frontier model development (e.g., Llama, LMMs)
  • Perceptual foundations for real-time embodied agents and conversational AI

Our team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year. To learn more about our research, visit https://ai.meta.com/research/.

Qualifications
  • Currently has or is in the process of obtaining a PhD degree in Computer Science, Electrical Engineering, Computer Vision, Machine Learning, Artificial Intelligence, relevant technical field, or equivalent
  • Research and/or work experience in video generation, computer vision, or multimodal AI
  • Experience with large-scale model training, post-training optimization techniques, and/or data curation
  • Experience in Python, C++, or other related languages, and deep learning frameworks (e.g., PyTorch, TensorFlow)
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
  • Demonstrated research and software engineering experience via internships, industry or academic work experience, coding competitions, or widely used contributions in open source repositories (e.g., GitHub)
  • Experience with video generation, video synthesis, or multimodal fusion techniques
  • Experience with video-language models and architectures relevant to video generation and post training
  • Proven track record of achieving significant results, as demonstrated by grants, fellowships, patents, or publications at leading workshops, journals, or conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV)
  • Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
  • Experience solving complex problems and evaluating alternative solutions, tradeoffs, and perspectives to determine a path forward
  • Experience working and communicating cross-functionally in a collaborative, interdisciplinary team environment
  • Intent to return to degree-program after the completion of the internship/co-op
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