Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) team to build world models, learn to understand and make predictions about the physical world, especially from video, and develop efficient algorithms for world model-based planning and control.
Requirements
- PhD degree in AI, computer science, data science, or related technical fields
- First-authored publications at peer-reviewed conferences, such as ICML, NeuRIPS, ICLR, CVPR, ICCV, CoRL, or similar
- Research background in machine learning, artificial intelligence, computational statistics, applied mathematics, or related areas
- Experience coding software and executing complex experiments
- Experience with Python and PyTorch
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), and Computer Vision (CVPR, ICCV, ECCV).
- Experience building systems based on machine learning and/or deep learning methods.
Responsibilities
- Leading, collaborating, and executing on research that pushes forward the state of the art in artificial intelligence
- Performing research that enables learning the semantics of data (images, video, text, audio, and other modalities)
- Working towards long-term research goals, while identifying immediate milestones
- Influencing progress of relevant research communities by producing publications
- Collaborating with scientists and engineers in a large cross-functional team
- Open source high quality code and produce reproducible research
Other
- 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 working and communicating cross functionally in a team environment.
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.
- Experience collaborating in a team environment on research projects
- Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
