Ai Research Engineer (Model Evaluation)

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 enable businesses to seamlessly integrate reserve-backed tokens across blockchains, providing secure, instant, and cost-effective digital transactions.

Transparency and trust underpin our operations.

Innovate with Tether

Tether Finance :

Our product suite features the trusted stablecoin

USDT

and digital asset tokenization services.

Tether Power :

We promote sustainable growth through eco-friendly energy solutions for Bitcoin mining.

Tether Data :

We develop AI and P2P solutions like

KEET

for secure data sharing.

Tether Education :

We democratize digital learning for individuals in the gig economy.

Tether Evolution :

We push technological boundaries to merge innovation with human potential.

Why Join Us?

Our global, remote team is passionate about fintech innovation.

If you excel in English communication and aspire to contribute to a leading platform, Tether is your place.

Are you ready to be part of the future?

About the job :

As part of our AI model team, you will develop evaluation frameworks for pre-training, post-training, and inference, focusing on metrics like accuracy, latency, and memory usage.

Your work spans resource-efficient models to complex multi-modal architectures.

You will collaborate with cross-functional teams to share findings, build evaluation pipelines, and set industry standards for AI model quality, ensuring real-world applicability and continuous improvement.

Responsibilities :

Develop and deploy evaluation frameworks assessing models at all lifecycle stages.

Create datasets and benchmarks for measuring model robustness and quality.

Collaborate with teams to align evaluation metrics with business goals and present insights via dashboards.

Analyze evaluation data to optimize model performance and resource utilization.

Refine evaluation methodologies through iterative research and stay updated on emerging techniques.

Minimum requirements :

A degree in Computer Science or related field; PhD preferred, with a record of AI R&D and publications.

Experience designing and evaluating AI models across lifecycle stages, with proficiency in evaluation frameworks.

Strong programming skills and familiarity with benchmarking pipelines, performance metrics, and resource optimization.

Ability to conduct experiments, research, and stay current with new techniques.

Experience working with cross-functional teams, translating technical insights into actionable strategies.

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