Research Intern, Machine Learning - Audio (PhD University Student)

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.

Facebook Reality Labs in Redmond, WA is looking for exceptional interns to help us make audio in augmented reality and virtual reality realistic. The goal of this project is high-accuracy 3D reconstruction of rigid objects for a novel application related to personalized AR/VR experience. Come join us as we make AR and VR happen!
Our internships are sixteen (16) to twenty four (24) weeks long and we have various start dates throughout the year.

RESPONSIBILITIES

  • Research, model, design, and/or build novel reconstruction architectures.
  • Collaborate with researches and engineers across diverse disciplines.
  • Communication of research agenda, progress and results.
MINIMUM QUALIFICATIONS
  • Pursuing a PhD in Computer Science, Robotics, Applied Math or a related STEM field
  • Currently enrolled in a full time degree program and returning to the program after the completion of the internship
  • Experience with numerical optimization, and machine learning
  • Interpersonal skills: cross-group and cross-culture collaboration
  • Able to obtain work authorization in the U.S. between January 1, 2019 and December 31, 2019
PREFERRED QUALIFICATIONS
  • Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
  • High levels of creativity and quick problem solving capabilities
  • Experience with machine learning libraries such as PyTorch, TensorFlow, etc.
  • Proven track record of achieving results as demonstrated in accepted papers at top computer vision and machine learning related conferences such as CVPR, ECCV, NIPS, etc.


Back to top