Senior Research Engineer Multimodal Video Foundation Model

About Us

At Tether, we're not just building products, we're pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.

About the Company

Tether Finance features the world's most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.

Our innovative portfolio includes:

• Tether Power: Driving sustainable growth with eco-friendly Bitcoin mining solutions
• Tether Data: Fueling breakthroughs in AI and peer-to-peer technology with solutions like KEET
• Tether Education: Democratizing access to digital learning
• Tether Evolution: Pushing boundaries at the intersection of technology and human potential

About the Role

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.

Requirements

• 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
• First-author publications at leading AI conferences such as CVPR, ICCV, ECCV, ICML, ICLR, NeurIPS etc.

Nice to Have

• 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.

Benefits

Pay in Crypto

Location

London, United Kingdom

Compensation

$90k - $150k (estimated)