Research Scientist Intern, Assistant Multimodal (PhD)


Redmond, WA, USA Remote


Nov 10

This job is no longer accepting applications.

Facebook is seeking Research Interns to join our Assistant AI teams in Redmond, WA, and Burlingham, CA. These teams are part of the Facebook Research and FRL Assistant organizations within Facebook, working to advance the state of the art in multimodal learning and media understanding, and deploy these systems at scale for various applications in the production system.

Our research spans multiple areas across multimodal machine learning, including deep learning/neural networks, video/image and text joint learning, multimodal fusion, multimodal conversational AI, and cross-domain transfer learning.

As a Research Intern, you will help us develop and apply cutting-edge machine learning algorithms to a wide range of media understanding challenges at Facebook. The duration of this internship is 16 weeks with Summer, Fall, and Winter start dates. Internships will be awarded on a rolling basis and candidates are encouraged to apply early.Research Scientist Intern, Assistant Multimodal (PhD) Responsibilities

  • Perform research to advance the science and technology of intelligent machines.
  • Develop novel and accurate multimodal algorithms and systems, leveraging deep learning and machine learning on big data resources.
  • Contribute research that can be applied to Facebook product development.
  • Analyze and improve efficiency, scalability, and stability of various deployed systems.

Minimum Qualifications

  • Currently has, or is in the process of obtaining a PhD degree Computer Vision, Machine Learning, or related fields.
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
  • 1 year experience in PyTorch, Python or C/C++.
  • Research and/or work experience in machine learning, deep learning, computer vision, and/or Natural Language Processing.

Preferred Qualifications

  • Comfort 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 CVPR, ICCV, ECCV, ACL, EMNLP, NAACL, AAAI, ICML, NeurIPS, ICLR or similar.
  • 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.
  • Experienced with the development of enterprise level AI, machine learning and deep learning platforms involving big data management and GPU compute.
  • Experienced with training deep neural networks for key Speech tasks such as speech recognition, speech translation, classification, semantic segmentation, object detection, etc.

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