Research Scientist, World Modelling | Chercheur scientifique, modélisation du monde

Meta•Montreal, QC

7d•CA$104,000 - CA$148,000

About The Position

Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) team, one of the top industrial AI research organizations in the world. In this role, you will help build world models that learn to understand and make predictions about the physical world, especially from video, and develop efficient algorithms for world model-based planning and control. Our team is driving an ambitious agenda to train and use world models for embodied agents. We innovate across related topics including self-supervised learning from video, predictive models, model-based reinforcement learning, and model-predictive control. We accomplish this by advancing research across the stack, including data curation, training large-scale state-of-the-art models, and designing robust benchmarks. We are looking for research scientists who share our passion for building efficient, scalable, and robust models of the world that will be part of the next paradigm in AI models.

Requirements

Currently has, or is in the process of obtaining, a PhD degree in AI, computer science, data science, robotics, or related technical fields
First-authored publications at peer-reviewed conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, CoRL, RSS, or ICRA, or similar
Research background in machine learning, artificial intelligence, robot learning, computational statistics, applied mathematics, or related areas
Experience coding software and executing complex experiments
Experience with Python and PyTorch

Nice To Haves

Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward
Track record of achieving significant results as demonstrated by grants, fellowships, patents, or publications at leading conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), or Computer Vision (CVPR, ICCV, ECCV)
Experience with self-supervised learning from video, predictive models, model-based reinforcement learning, or model-predictive control
Experience building systems based on machine learning or deep learning methods
Experience manipulating and analyzing complex, large-scale, high-dimensionality data from varying sources
Experience collaborating in a team environment on research projects

Responsibilities

Lead, collaborate, and execute on research that pushes forward the state of the art in world modelling and artificial intelligence
Perform research that enables learning the semantics of data across modalities including images, video, text, and audio
Work towards long-term research goals while identifying immediate milestones
Develop and evaluate novel architectures and training methods for learning predictive models of visual, physical, or multimodal environments
Explore applications of world models to planning, prediction, control, and decision-making for embodied agents
Influence progress of relevant research communities by producing publications at peer-reviewed venues
Collaborate with scientists and engineers in a large cross-functional team
Open source high quality code and produce reproducible research
Support recruiting efforts by engaging with potential candidates and sharing insights about world modelling research at Meta