Remote AI Research Engineer: LLM & Multi-Modal Pre-Training

Tether Ltd.; Dublin; Hybrid; EUR 134,000 - 188,000; Full time

Job summary

Tether Ltd. is seeking a senior AI model researcher to advance architecture for large-scale LLM and multi-modal systems. You will lead pre-training, alignment, data strategy, and experiments on distributed GPU clusters, shaping the next generation of intelligent models.

Join a global, remote-first team and contribute to cutting-edge research, with publication potential and a focus on efficiency, scalability, and practical deployment across platforms.

Qualifications

• PhD in NLP/ML or related field; strong AI R&D track record.
• Experience leading large-scale LLM or multimodal pre-training.
• Proficiency with distributed training tools and PyTorch.

Responsibilities

• Large-Scale Pre-Training: conduct foundational pre-training for LLMs and multi-modal models on large distributed servers with thousands of NVIDIA GPUs.
• Architecture & Alignment Innovation: design and scale architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence.
• Data Strategy: source, filter and curate massive-scale textual and multi-modal datasets and build robust data pipelines.
• Experimental Research: run experiments, analyze results, and refine training methodologies for performance and efficiency.
• Optimization & Debugging: identify bottlenecks in efficiency and multi-modal alignment during long training runs.
• System Scalability: advance distributed training systems for scalability and hardware efficiency.

Skills

LLM

Multi-Modal

Pre-training

Distributed training

PyTorch

Hugging Face

NVIDIA GPUs

Research methodology

Education

PhD in NLP or ML

Tools

Hugging Face Transformers

Distributed training frameworks

Job description

Tether Ltd. is seeking a senior AI model researcher to advance architecture for large-scale LLM and multi-modal systems. You will lead pre-training, alignment, data strategy, and experiments on distributed GPU clusters, shaping the next generation of intelligent models.

Join a global, remote-first team and contribute to cutting-edge research, with publication potential and a focus on efficiency, scalability, and practical deployment across platforms.