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About the role

Research Scientist Intern, Photorealistic Telepresence (PhD) at Meta

Required Skills

pythonpytorchcomputer visioncomputer graphicsmachine learningdeep learninggenerative aillms3d data

About the Role

Research Scientist Intern focused on photorealistic telepresence and autonomous social agents in VR/AR. Responsibilities include solving research problems in computer vision, graphics, and AI, collaborating across disciplines, and communicating research progress. The role involves working on generative AI models, motion synthesis, and multimodal LLMs.

Key Responsibilities

  • Solve research problems in enabling photorealistic telepresence and autonomous social agents
  • Collaboration with and support of other researchers across various disciplines
  • Communication of research agenda, progress, and results
  • Work on generative AI models for image and video synthesis
  • Develop motion and behavior synthesis for digital humans

Required Skills & Qualifications

Must Have:

  • Currently has or is in process of obtaining PhD in Computer Science, Computer Vision, Computer Graphics, Robotics, Machine Learning or related field
  • Experience with solving inverse problems in imaging emphasizing modeling and algorithm development
  • 2+ years of experience with Machine Learning for solving computer vision and computer graphics problems
  • Experience with deep learning frameworks such as Pytorch and TensorBoard
  • Experience with scientific programming languages such as Python
  • Must obtain work authorization in country of employment

Nice to Have:

  • Proven track record of achieving significant results as demonstrated by patents and first-authored publications at leading conferences
  • Intent to return to degree-program after completion of internship
  • Experience working and communicating cross functionally in team environment
  • Demonstrated software engineer experience via internship, work experience, or open source contributions
  • Experience with systems building in Python or C++
  • Experience with large-scale generative models such as LLMs and video diffusion models
  • Experience with Machine Learning for 3D data (meshes, point clouds, gaussian splatting, voxels)
  • Experience with Machine Learning for audio and visual synthesis