AI Research Scientist – Computer Vision and Machine Learning (Paris)

Meta is seeking Research Scientists to join its Fundamental AI Research (FAIR) organization, an organization focused on making significant advances in AI. We publish groundbreaking papers and release frameworks/libraries that are widely used in the open-source community. Recent examples include the DINOv2 family of visual models and their applications. We closely collaborate with other organizations at Meta to bring the latest research findings to production. We are seeking talented researchers with experience in machine learning and computer vision to join the Paris site and work with us on conducting research on self-supervised learning and developing the next generation of unsupervised visual foundation models. Researchers will drive impact by (1) publishing state-of-the-art research papers, (2) open-sourcing high-quality code and reproducible results for the community, and (3) bringing the latest research to Facebook products for connecting billions of users. The chosen candidate(s) will work with a diverse and highly interdisciplinary team of scientists, engineers, and cross-functional partners and access cutting-edge technology, resources, and research facilities.

AI Research Scientist – Computer Vision and Machine Learning (Paris) Responsibilities:

• Lead research on the next generation of self-supervised learning algorithms for training state-of-the-art visual representations.
• Conduct research towards long-term ambitious research goals while identifying intermediate milestones.
• Influence the progress of relevant research communities by producing publications.
• Contribute research that can be applied to Meta product development.
• Lead and collaborate on research projects within a globally based team

Minimum Qualifications:

• Ph.D. degree in Computer Science, Mathematics, or a similar quantitative field.
• First-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR, ECCV, ICCV, CVPR).
• Extensive experience with deep learning, neural network design, modeling, and large-scale optimization.
• Familiarity with pytorch, python, bash, and distributed computing.
• Ability to communicate complex research both in writing and orally for public audiences of peers.

Preferred Qualifications:

• High-impact publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR, ECCV, ICCV, CVPR), as witnessed by citations and other signs of influencing the research community.
• Experience in developing and debugging beyond ML applications.
• Experience working in an industry research environment and applying research to industrial problems.
• Experience in coordinating the research of Ph.D. students or other researchers.

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