AI Research Engineer, LLM and Multimodal Pretraining at Tether
Confirmed open
Research and scale language and multimodal model pretraining across distributed NVIDIA GPU infrastructure. The employer lists Hanoi, Vietnam.
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Tether- Location
- Hanoi, Vietnam
- Employment
- fulltime_permanent
- Work arrangement
- remote
- Technologies
- PyTorch
Role overview
Tether’s AI model team seeks a researcher to improve architectures and pretraining for language and multimodal models. Work spans text, vision and audio data, with large distributed training runs and attention to efficiency and cross-modal alignment. Each requisition specifies its own remote location.
Responsibilities
- Run foundational LLM and multimodal pretraining across distributed, multi-node NVIDIA GPU systems.
- Prototype and scale architectures, tokenizers and cross-modal alignment methods.
- Source, filter and curate large text and multimodal datasets and build reliable training data pipelines.
- Design experiments, analyse results and improve performance and token efficiency.
- Debug long-running training bottlenecks and improve the scalability and hardware efficiency of distributed systems.
Qualifications
- Computer science or related degree; a PhD in NLP or machine learning and research publications are preferred.
- Hands-on contribution to large-scale LLM or multimodal pretraining on distributed GPU infrastructure.
- Practical familiarity with distributed training frameworks and model architecture changes that improve intelligence, efficiency or scalability.
- Strong PyTorch and Hugging Face experience in model development, continued pretraining and deployment.
About Tether
Tether develops digital-token products, including USDT, alongside projects in peer-to-peer communications and AI. The employer describes a globally distributed remote team.
How to apply
Review the original posting and apply through the employer’s careers page.
View source and applyApply directlySource checked: 2026-09-29
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