Fundamental AI Research Scientist – FAIR Full-time

Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) team, a research organization focused on advancing the state-of-the-art in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, computational linguistics, and applied mathematics, particularly including topics such as deep learning, reinforcement learning, representation learning, multimodality, multilingual language models, AI safety, foundations of generative modeling and social implications of AI. The ideal candidate will have a keen interest in producing new science to understand intelligence and technology towards achieving advanced machine intelligence.

Fundamental AI Research Scientist – FAIR Responsibilities

• Perform research to advance the science and technology of intelligent machines.
• Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities).
• Work towards long-term ambitious research goals, while identifying immediate milestones.
• Influence progress of relevant research communities by producing publications.
• Open source high quality code and produce reproducible research.

Minimum Qualifications

• A PhD in AI, computer science, data science, or related technical fields.
• Experience holding an industry, postdoctoral, faculty, or government researcher position.
• Research background in machine learning, artificial intelligence, computational statistics, or applied mathematics, or related areas.
• Research publications reflecting experience in theoretical or empirical research.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications

• Research and engineering experience demonstrated via publications, grants, fellowships, patents, internships, work experience, open source code, and / or coding competitions.
• First-authored publications at peer-reviewed conferences, such as ICML, NeuRIPS, ICLR, ACL, EMNLP, FacCT, CCS, IEEE S&P, and other similar venues.
• Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view.
• Experience collaborating in a team environment on research projects.
• Experience communicating research findings to public audiences of peers.