Meta is looking for a Research Engineer 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 research engineers, particularly with background and experience in Computer Vision and Machine Learning to join the Paris site and work with us to scale self-supervised learning approaches and enable the development of the next generation of unsupervised visual foundation models. Researchers will drive impact by (1) contributing to state-of-the-art research publications, (2) open-sourcing high-quality code and reproducible results for the community, and/or (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 and engineers, and cross-functional partners and access cutting-edge technology, resources, and research facilities.
Research Engineer – Computer Vision Responsibilities:
- Lead, collaborate and execute on platforms, data and/or research that allows pushing forward the state-of-the-art in training visual representations through self-supervision
- Drive software design, implementation and evaluation of research solutions
- Propose experimental design, conduct evaluation and reporting of results
- Work with, create and evaluate large visual datasets
Minimum Qualifications:
- Master’s degree in Computer Science, Computer Engineering or relevant technical field
- 3+ years of industry experience in Computer Vision and/or Machine Learning
- Proficiency in software development in Python, C++ or similar
- Experience with machine learning models, and frameworks such as PyTorch, TensorFlow or similar
Preferred Qualifications:
- Ph.D. degree in Computer Vision and/or Machine Learning or relevant technical field
- Publication record at peer-reviewed AI conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML or similar)
- 4+ years of industry, academic, or government lab experience in Computer Vision and/or Machine Learning and applying research to industrial problems
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