Research Scientist, Multi-Modal Human Understanding

Meta•Pittsburgh, PA

34d•$122,000 - $181,000

About The Position

Meta is seeking a Research Scientist to advance multi-modal AI technologies for human understanding and synthesis. In this role, you will develop Vision-Language Models (VLMs) and video foundation models that enable machines to perceive, interpret, and generate rich representations of human behavior, expression, and interaction. Your research will span multi-modal reasoning, video understanding, and generative synthesis, enabling more natural and intuitive human-computer interaction at scale.

Requirements

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
2+ years of experience in multi-modal AI research, including hands-on work with Vision-Language Models, video understanding, or human-centric AI systems
2+ years of experience implementing and training large-scale neural networks using frameworks such as PyTorch, with experience on transformer-based architectures
Experience designing and executing experiments to evaluate multi-modal model performance, including quantitative analysis across vision, language, and video benchmarks
Experience writing production-quality or research-quality code in Python for multi-modal AI applications

Nice To Haves

Experience developing or fine-tuning Vision-Language Models for human understanding tasks
Experience with video foundation models, temporal transformers, or large-scale video pretraining
Track record of contributing to published multi-modal AI research at venues such as CVPR, ICCV, or NeurIPS
Experience with generative models for human synthesis including diffusion models, GANs, or autoregressive models for video or motion generation

Responsibilities

Design and implement novel multi-modal architectures that fuse vision, language, and temporal signals for holistic human understanding
Develop and train Vision-Language Models (VLMs) for tasks including visual question answering, image-text reasoning, and grounded human-centric understanding
Build video foundation models capable of temporal reasoning, action synthesis and long-form video synthesis with applications to human behavior synthesis
Research generative synthesis techniques for human-centric content including video generation, motion synthesis, and multi-modal content creation
Conduct rigorous experiments to evaluate model performance across diverse benchmarks, analyze failure modes, and iterate on architectures to improve accuracy and generalization
Contribute to the full research lifecycle from problem formulation and dataset curation through model development and evaluation