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 speech/audio, multimodality, and machine learning. The ideal candidate should have a keen interest in producing new, open science to further advance multimodal (audio+video focused) generative modeling research. Postdoctoral positions are one to two year fixed-term positions.Postdoctoral Researcher, FAIR Responsibilities
- Perform research to push the scientific and technological frontiers of multimodal generative modeling.
- Invent/improve large-scale data-driven paradigms for multimodal generation.
- Enable reasoning with multimodal understanding and generation systems.
- Develop the next generation of platforms for AI & multimodal research.
Minimum Qualifications
- Currently has or is in the process of obtaining a PhD degree in the field of Machine Learning, Speech and Audio Processing, Multimodal Understanding and Generation, Generative Modeling, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Experience in training and use of large language models or diffusion models
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading ML conferences (NeurIPS, ICML, ICLR), Speech (Interspeech, ICASSP), and/or Computer Vision (CVPR, ECCV, ICCV)
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- 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.
- Experience in deep learning frameworks (such as PyTorch, TensorFlow), C, C++, Python.
- Experience in AI frameworks like Hugging Face, fairsesq or other systems.
Preferred Qualifications
- 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 building systems based on machine learning and/or deep learning methods.
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
- Experience working and communicating cross functionally in a team environment.
- Research experience in machine learning, representation learning, optimization, statistics, applied mathematics, or data science.