Senior AI Engineer - Data & Infrastructure for Multimodal Models (100% Remote)

Senior AI Engineer - Data & Infrastructure for Multimodal Models (100% Remote)

Join Tether and Shape the Future of Digital Finance

At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses to seamlessly integrate reserve-backed tokens across blockchains.

Innovate with Tether

Tether Finance : Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide.

Tether Power : Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices.

Tether Data : Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET .

Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies.

Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible.

Why Join Us?

Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds.

About The Job

We're seeking experienced AI infrastructure Engineers to design and implement robust, scalable pipelines for massive data workloads.

Responsibilities

• Build and scale high-throughput data infrastructure optimized for video and multimodal content processing across large GPU clusters.
• Design core preprocessing algorithms for video, audio, text, and image modalities.
• Build automated acquisition pipelines for sourcing large-scale video datasets.
• Architect robust systems for scalable evaluation and annotation.
• Collaborate with model researchers to co-design video model architectures and training schedules.
• Optimize distributed data loading and pipeline throughput for training at scale.
• Manage infrastructure to support experiment tracking, model versioning, and cross-team deployment workflows.
• Support backend engineering across research, product, and creative teams.

Preferred Qualifications

Important information for candidates

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