AI Research Engineer (Pre-training - LLM & Multi-Modal)

Responsibilities

• Conduct foundational pre-training for LLMs and Multi-Modal models on large, distributed servers with thousands of NVIDIA GPUs
• Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers
• Source, filter, and curate massive-scale textual and multi-modal datasets and establish robust data pipelines
• Execute experiments, analyze results, and refine training methodologies for optimal performance
• Investigate, debug, and eliminate bottlenecks in model efficiency and multi-modal alignment stability
• Contribute to the advancement of distributed training systems for hardware efficiency

Requirements

• Degree in Computer Science or related field (PhD in NLP or Machine Learning preferred)
• Track record in AI R&D with publications in A* conferences
• Hands-on experience with large-scale LLM or Multi-Modal pre-training on distributed GPU clusters
• Practical experience with large-scale distributed training frameworks and tools
• Deep knowledge of state-of-the-art transformer and non-transformer modifications
• Strong expertise in PyTorch and Hugging Face libraries

About the Company

Tether is a leader in digital finance, pioneering solutions that empower businesses to integrate reserve-backed tokens across blockchains. From the world's most trusted stablecoin, USDT, to cutting-edge AI and peer-to-peer technology, Tether is shaping the future of the global financial revolution.