Senior Research Engineer

About the job

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. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: data curation, strengthening baselines, identifying and resolving existing pre-training bottlenecks to push the limits of model performance.

Responsibilities

• 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 .

Nice to have skills:

• 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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