Research Scientist Intern, AI Core Machine Learning

4 days ago

Bellevue, Washington, United States META Full time

Job Summary

Meta is seeking a highly motivated Research Scientist Intern to join our AI Core Machine Learning team. As a Research Scientist Intern, you will have the opportunity to work on cutting-edge AI research projects and contribute to the development of new machine learning algorithms and systems.

Responsibilities

  • Develop novel state-of-the-art algorithms and corresponding systems, leveraging various deep learning techniques
  • Analyze and improve various aspects of the corresponding algorithms and systems, including efficiency, scalability, stability, fairness, security, and privacy
  • Perform state-of-the-art research to advance the science and technology of Machine Learning and Artificial Intelligence
  • Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results
  • Publish research results and contribute to research that can be applied to Meta product development

Requirements

  • Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a relevant technical field
  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
  • Experience with Python, C++, C, Java, or other related languages
  • Experience with deep learning frameworks such as PyTorch or TensorFlow

Preferred Qualifications

  • Intent to return to degree program after the completion of the internship/co-op
  • Proven track record of achieving significant results, as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences
  • Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches
  • Experience building large-scale machine learning systems and training with large datasets
  • Experience communicating complex research in a clear, precise, and actionable manner
  • Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open-source repositories
  • Experience working and communicating cross-functionally in a team environment

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