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Postdoctoral Researcher, Trustworthy ML (PhD)

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1mo ago

💼 Graduate Job

San Francisco +2

AI generated summary

  • You need a PhD in AI/ML or related field, experience with learning frameworks and C++, and a strong publication record. Must have work authorization and proven track record of achievements. Experience with large scale data, problem solving, and privacy/fairness is preferred.
  • You will engage with FAIR researchers to develop and implement a research agenda, publish top-tier works, and identify impactful projects in unexplored domains, making external impact.

Graduate Job

Research & Development, DataSan Francisco, New York, Menlo Park


  • Meta is seeking a Postdoctoral Researcher to join Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence and machine learning.
  • In particular, we are looking for candidates interested in exploring the impact of data curation on privacy, fairness, and robustness as well as other topics in privacy and security of large-scale multi-modal models. Potential research directions may investigate whether data curation has disparate impacts across groups, how data design impacts the ability of adversaries to compromise privacy, whether data choices can improve fairness, or other directions related to these topics. Projects will be determined together with the Postdoc, supervisor, and other researchers in FAIR.
  • We are seeking candidates with a keen interest in developing novel approaches that lead to better solutions for core machine learning problems, with a focus on trustworthy aspects of machine learning, such as privacy, fairness and robustness.
  • Postdoc positions are one to two year fixed-term positions.


  • Minimum Qualifications:
  • Currently has or is in the process of obtaining a PhD degree in the field of Artificial Intelligence, Machine Learning, Operation Research or a related field, or equivalent practical experience. Degree must be completed prior to joining Meta
  • Experience in learning frameworks (such as PyTorch, TensorFlow), C, C++, Python.
  • Basic research experience with publications in conferences/journals in the related fields.
  • Have basic research experience with publications in conferences/journals in the related fields
  • Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
  • Publication record in Machine learning or related area.
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
  • Preferred Qualifications:
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR). Other closely related track records (e.g., Operation Research, MLSys) will also be considered in a case-by-case manner.
  • Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
  • Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
  • Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
  • Prior experience working with multimodal models or on privacy and fairness.

Education requirements

Currently Studying

Area of Responsibilities

Research & Development


  • Engage with the supervisor and other researchers in Fundamental AI Research (FAIR) to develop and implement research agenda, publish world-class research works, and make external impact.
  • Identify highly impactful projects in a complex and unexplored domain.


Work type

Full time

Work mode



San Francisco, New York, Menlo Park