Logo of Huzzle

Research Scientist Intern, AI Experimentation (PhD)

image

Meta

Feb 12

Applications are closed

  • Internship
    Full-time
    Off-cycle Internship
  • Software Engineering
  • Seattle, +1

Requirements

  • Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Computer Vision, Natural Language Processing, Reinforcement Learning, Optimization, Computational Statistics, Applied Mathematics, or related technical fields.
  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
  • Experience with adaptive online and offline experimentation methods.
  • Experience with Python, C++, C, Java, or other related languages.
  • Experience with research and building systems based on machine learning and/or deep learning methods.
  • Preferred Qualifications:
  • Intent to return to degree program after the completion of the internship/co-op.
  • Proven track record of achieving significant research results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, KDD, IJCAI, CVPR, ICCV, ACL, NAACL, ICASSP, or similar.
  • Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
  • Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches.
  • Strong interest in theoretical and empirical research and for answering hard questions with research.
  • Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources for large-scale training.
  • Experience working and communicating cross functionally in a team environment.

Responsibilities

  • Conduct state-of-the-art research to advance experimentation.
  • Contribute to research that leads to innovations in scalable machine learning systems.
  • Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
  • Collaborate with researchers and engineers across diverse disciplines, including communicating research plans, progress, and results.
  • Publish research results and contribute to research that can be applied to Meta product development.

Technology
Industry
10,001+
Employees
2004
Founded Year

Mission & Purpose

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.