Senior Research Engineer - Multimodal & Video Foundation Model

Overview

Senior Research Engineer - Multimodal & Video Foundation Model

As a member of the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field. You will have a deep expertise in video generation model architectures with a hands-on, research-driven approach.

• Pioneer multimodal and video-centric research that moves fast and breaks ground, contributing directly to usable prototypes and scalable systems.
• Design and implement novel AI architectures for multimodal language models, integrating text, visual, and audio modalities.
• Engineer scalable training and inference pipelines optimized for large-scale multimodal datasets and distributed GPU systems across thousands of GPUs.
• Optimize systems and algorithms for efficient data processing, model execution, and pipeline throughput.
• Build modular tools for preprocessing, analyzing, and managing multimodal data assets (e.g., images, video, text).
• Collaborate cross-functionally with research and engineering teams to translate cutting-edge model innovations into production-grade solutions.
• Prototype generative AI applications showcasing new capabilities of multimodal foundation models in real-world products.
• Develop benchmarking tools to rigorously evaluate model performance across diverse multimodal tasks.

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
• Expertise in Python & PyTorch, including practical experience working with the full development pipeline from data processing & data loading to training, inference, and optimization.
• Experience working with large-scale text data, or (bonus) interleaved data spanning audio, video, image, and/or text.
• Direct hands-on experience in developing or benchmarking at least one of the following topics: LLMs, Vision Language Models, Audio Language Models, generative video models

• PhD in Computer Vision, Machine Learning, NLP, Computer Science, Applied Statistics, or a closely related field
• Demonstrated expertise in computer vision, video generation foundation model and/or multimodal research.
• First-author publications at leading AI conferences such as CVPR, ICCV, ECCV, ICML, ICLR, NeurIPS etc.

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• Not Applicable

• Full-time

• Information Technology

• Technology, Information and Internet