Research Scientist Intern, AI Core Machine Learning (PhD)

Meta - Menlo Park, CA

Full-time - Intern

Menlo Park, CA

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About the position

The Research Scientist Intern in AI Core Machine Learning at Meta is a role designed for PhD candidates passionate about advancing artificial intelligence technologies. The intern will have the opportunity to develop state-of-the-art algorithms, conduct research, and collaborate with cross-functional teams to apply their findings to Meta's product development. This internship lasts between 12 to 24 weeks, providing a platform for significant contributions to the field of machine learning and AI.

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 relevant technical field.
• Must obtain work authorization in 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.

Nice-to-haves

• 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 such as NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, CCS, IEEE S&P, MLSys, or similar.
• 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 engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience working and communicating cross-functionally in a team environment.

Benefits

• $7,500/month to $11,333/month compensation
• Health insurance
• Paid holidays
• Flexible scheduling
• Professional development opportunities