Research Scientist, FAIR (PhD)

Meta is seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Developmental AI. Current machine learning algorithms can match human performance in a variety of tasks but require orders of magnitude more data. Developmental AI aims at building AI agents that learn autonomously from few amounts of real world data and interactions as children do. This covers the design of algorithms that leverage advanced machine learning techniques to improve robustness and sample efficiency, the building of datasets or simulators of ecological data, and benchmarks to compare how fast children and machines learn given similar input. The focus is on grounded language and communication. We publish groundbreaking papers and release frameworks/libraries that are widely used in the open-source community fostering the advancement of AI at its intersection with the study of natural intelligence. We seek researchers with expertise in AI and interest in cognitive science to join our research team to foster cutting-edge research in Developmental AI.

• Lead research to advance the science and technology of intelligent machines.
• Publishing state-of-the-art research papers in both high impact machine learning and cognitive science outlets.
• Conducting research that investigates how AI can improve the science of learning in biological organisms and vice versa.
• Work towards long-term research goals, while identifying intermediate milestones.
• Lead and collaborate on research projects within a globally based team.
• Open sourcing high quality code and reproducible results for the community.

• Currently has, or is in the process of obtaining, a PhD in mathematics, statistics, computer science, cognitive or language science with a background in both theoretical and empirical disciplines.
• Interest in cross-disciplinary communication towards conducting research in Developmental AI.
• Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures.
• Experience communicating complex research for public audiences of peers.
• Experience with deep learning frameworks such as Pytorch, Jax, or Tensorflow.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

• Proven track record of achieving significant results as demonstrated by grants, or fellowships, as well as publications in top AI conferences (NeurIPS, ICML, ICLR, etc.) and/or top cognitive (neuro)science journals.
• 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 solving analytical problems using quantitative approaches.
• Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
• Experience in utilizing theoretical and empirical research to solve problems.
• Experience doing optimization 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.