Job Description

As a Research Engineer focused on Multi-Modal Understanding, you will develop advanced algorithms that integrate computer vision with other modalities such as language, audio, and sensor data. You will also drive the curation of multi-modal datasets and ground truth annotation pipelines to support model training and evaluation. You will work closely with our research team to bring innovative multi-modal solutions to production, bridging the gap between visual perception and holistic contextual understanding for immersive applications.

Responsibilities
Design and implement multi-modal understanding systems that combine vision, language, and other sensory inputs to enable richer contextual awareness
* Develop algorithms for cross-modal learning, fusion, and reasoning to improve human-AI interaction
* Lead the curation and management of multi-modal datasets, ensuring data quality and diversity across vision, language, and sensor modalities
* Design and oversee ground truth annotation workflows and quality assurance processes for multi-modal data
* Complete medium to large features spanning multiple tasks independently with minimal to no guidance
* Collaborate with researchers and engineers across computer vision and machine learning teams to drive multi-modal innovation
* Develop well-organized code with proper testing and documentation, building production-ready multi-modal systems

Qualifications
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
* 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
* Proven experience with C++ and/or Python, including experience with modern features
* Experience working with deep learning frameworks such as PyTorch and TensorFlow
* Demonstrated experience working collaboratively in cross-functional teams Master's degree in Computer Science, Computer Vision, Machine Learning, or related field
* Experience with vision-language models or multi-modal transformers
* Publications or contributions to multi-modal understanding research
* Familiarity with large language models and their integration with visual understanding systems
* Experience with data curation, annotation tools, or ground truth labeling pipelines