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 Remote — India.

Tether

Location: Remote — India
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

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Source checked: 2026-09-29

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