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 solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, at a fraction of the cost. Transparency is our core value, ensuring trust in every transaction.

Innovate with Tether

Tether Finance: Our product suite features the trusted stablecoin, USDT, used by hundreds of millions, alongside digital asset tokenization services.

But that’s just the beginning:

Tether Power: Optimizing excess power for eco-friendly Bitcoin mining across diverse facilities.

Tether Data: Enhancing AI and peer-to-peer tech with solutions like KEET, our secure data sharing app.

Tether Education: Making digital learning accessible to empower individuals in the digital economy.

Tether Evolution: Merging technology and human potential to push innovation boundaries.

Why Join Us?

Our global, remote team is passionate about fintech innovation. Join us to work with top minds, set new standards, and make a significant impact. We value excellent English communication skills and a drive to contribute to our innovative platform.

Are you ready to be part of the future?

About the job:

As part of our AI model team, you will develop evaluation frameworks and benchmark methodologies for pre-training, post-training, and inference, ensuring models are responsive, efficient, and reliable. You will work on models from resource-constrained to multi-modal architectures involving text, images, and audio.

You should have expertise in advanced model architectures, evaluation practices, and developing metrics for accuracy, latency, throughput, and memory footprint. Your role involves designing, testing, and implementing evaluation strategies, collaborating with cross-functional teams, and creating performance dashboards to drive continuous improvement and industry-leading standards in AI model quality.

Responsibilities:

• Develop and deploy evaluation frameworks assessing models at all stages, tracking key performance metrics.
• Create evaluation datasets and benchmarks reflecting real-world scenarios to ensure robustness.
• Collaborate with product, engineering, and data teams to align evaluation metrics with business goals and present insights via dashboards.
• Analyze evaluation data to identify bottlenecks and propose optimizations for resource efficiency and scalability.
• Conduct experiments to refine evaluation methodologies, staying current with emerging techniques to enhance model reliability.

Minimum qualifications:

• A degree in Computer Science or related field; PhD in NLP, Machine Learning, or a related area with publications in top conferences preferred.
• Experience designing and evaluating AI models across lifecycle stages, with proficiency in developing evaluation frameworks.
• Strong programming skills and experience with benchmarking pipelines and performance metrics.
• Ability to conduct iterative experiments, stay updated with trends, and improve evaluation practices.
• Experience working with cross-functional teams and translating technical findings into actionable insights.