AI Research Lead - Pre-training: Tether

Tether is a global financial technology company pioneering a financial revolution through reserve-backed tokens and blockchain technology. Beyond its well-known stablecoin (USDT), Tether has divisions focused on AI and peer-to-peer technology (Tether Data), sustainable Bitcoin mining (Tether Power), and digital education.

They are seeking a senior Pre-Training Lead to own and scale their model development pipeline. This role is at the heart of their AI efforts, focusing on transforming public data into state-of-the-art (SOTA) foundation models. You will play a critical role in driving the technical direction for pre-training strategies and will have the opportunity to lead ambitious projects to advance open-source development and the global AI community.

Responsibilities
Lead the strategy and execution of all pre-training activities, including dataset building and pre-training experiments.

Build LLM and multimodal foundation models from scratch.

Design robust evaluation pipelines to measure model quality, performance, and user experience.

Build and manage a team of engineers and researchers to scale pre-training infrastructure.

Collaborate with infrastructure, data, and product teams to ensure fast iteration cycles.

Monitor advancements in pre-training research and incorporate novel techniques.

Contribute to the AI research community through publications, open-source contributions, and conference participation.

Communicate technical insights and updates effectively to executive leadership and stakeholders.

Requirements
Minimum Qualifications:

PhD, MS, or equivalent experience.

Hands-on experience in SOTA end-to-end pre-training projects and solutions.

5+ years of experience in managing or leading 10+ research & engineer teams.

Hands-on experience building end-to-end LLM and multimodal foundation models on thousands of multi-node GPUs.

Proficiency in modern deep learning and pre-training frameworks & libraries.

Excellent communication and interpersonal skills.

Preferred Qualifications:

A strong history of delivering innovation in the large-scale pre-training space.

Ability to develop a long-term vision and execute strategies at scale.

Experience with VP-level presentations and reporting.

Published papers in top AI conferences (e.g., ACL, NIPS, ICML, ICLR, CVPR, etc.).