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Research scientist intern

United States, Menlo Park 7650.00 - 12134.00 USD / Month · Job Posted March 22, 2026
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Job Description

Meta is seeking Research Interns to join our AI Solutions and Automation (ASA) Team. The ASA AI Exploration Team is a dynamic, applied research group focused on rapid exploration, post-training, and deployment of SOTA GenAI techniques. We are seeking individuals passionate in areas such as post-training particularly LLM post-training using reinforcement learning and reasoning, Agent post-training and long-horizon alignment, speculative decoding, Test-time scaling and adaptive compute. Our interns have an opportunity to work on high-impact projects, contribute to the team’s culture, and help shape the future of AI at Meta. Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.

Job Responsibility

  • Develop novel SOTA generative AI algorithms and systems, leveraging deep learning techniques
  • Analyze and improve efficiency, scalability, and stability of deployed algorithms
  • Advance the science and technology of intelligent machines through research
  • Enable learning the semantics and training generative models of data (images, video, 3D, text, audio, and other modalities)
  • Disseminate research results and publish in top tier conference

Requirements

  • Currently pursuing a Ph.D. in Computer Science, Artificial Intelligence, Generative AI, or a relevant technical field
  • Experience with Python, C++, C, Java, or related languages
  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
  • Experience building systems based on machine learning and/or deep learning methods

Nice to have

  • Intent to return to the degree program after the completion of the internship/co-op
  • Proven track record of achieving significant results (grants, fellowships, patents, first-authored publications at leading workshops/conferences: NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, ECCV, etc.)
  • Experience working and communicating cross-functionally in a team environment
  • Experience advancing AI techniques, including contributions to open source libraries/frameworks in computer vision or related fields
  • Publications or experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science
  • Experience solving analytical problems using quantitative approaches
  • Experience setting up ML experiments and analyzing their results
  • Experience manipulating and analyzing complex, large-scale, high-dimensionality data from varying sources
  • Experience utilizing theoretical and empirical research to solve problems
  • Experience with deep learning frameworks

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