Research Scientist Intern, Fair - Language & Multimodal Foundations (phd)

Meta Meta · Big Tech · Menlo Park, CA +2

Research intern at Meta's FAIR focusing on fundamental AI research in language and multimodal foundations, aiming to make core algorithmic advances and apply them at scale. The role involves research in NLP, audio, speech, computer vision, ML, deep learning, and RL, with opportunities for publication.

What you'd actually do

  1. Perform research that enables learning the semantics of data (specifically text, audio, images, video, and other modalities)
  2. Brainstorm with research mentors, review literature and existing solutions of a challenging real-world research problem
  3. Develop novel solutions, implement prototypes, and perform extensive experiments to test the proposed solutions in meaningful benchmarks and metrics, analyze the results and verify the conclusions
  4. Draft and polish research reports and/or publications
  5. Present research outcomes to internal and/or external audiences

Skills

Required

  • Python
  • C++
  • work authorization in the country of employment
  • return to degree-program after the completion of the internship/co-op

Nice to have

  • Natural Language Processing
  • Speech Processing
  • Computer Vision
  • Machine Learning
  • Deep Learning
  • Artificial Intelligence
  • machine translation
  • speech translation
  • natural language understanding and generation
  • language modeling
  • pretraining and post-training
  • low-resource NLP
  • question answering
  • dialogue
  • cross-lingual and cross-domain transfer learning
  • multimodal understanding, reasoning and generation
  • Reinforcement Learning
  • manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
  • utilizing theoretical and empirical research to solve problems
  • working and communicating cross functionally in a team environment

What the JD emphasized

  • publications at leading workshops or conferences in Speech & Language
  • publications at leading workshops or conferences in Computer Vision
  • publications at leading workshops or conferences in Machine Learning

Other signals

  • fundamental advances
  • core algorithmic advances
  • novel solutions