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

Tether Ltd.; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Tether Ltd. is seeking a senior AI researcher to drive architecture development for cutting-edge LLM and multi-modal models. You will optimize pre-training procedures, improve cross-modal alignment, and push the boundaries of scalable AI on massive GPU clusters.

You will apply deep expertise in transformer models, leverage PyTorch and Hugging Face, and contribute to data strategies, experiments, and system scalability to advance state-of-the-art capabilities in digital finance AI.

Qualifications

• PhD in NLP/ML or related field with strong AI R&D track record.
• Hands-on with large-scale LLM/Multi-Modal pre-training on thousands of GPUs.
• Deep knowledge of transformer and non-transformer models for efficiency.
• Proficiency in PyTorch and Hugging Face for model development and deployment.

Responsibilities

• Lead large-scale pre-training for LLMs and multi-modal models on distributed GPU clusters.
• Design and prototype novel architectures and alignment strategies to improve model performance.
• Source and curate large-scale multi-modal datasets; build robust data pipelines.
• Plan and execute experiments; analyze results; iterate training methods for efficiency.

Skills

LLM & multi-modal

PyTorch

Hugging Face

Distributed training

Research publications

Education

PhD in NLP / ML

CS degree

Tools

NVIDIA GPUs

Distributed training frameworks

Job description

Tether Ltd. is seeking a senior AI researcher to drive architecture development for cutting-edge LLM and multi-modal models. You will optimize pre-training procedures, improve cross-modal alignment, and push the boundaries of scalable AI on massive GPU clusters.

You will apply deep expertise in transformer models, leverage PyTorch and Hugging Face, and contribute to data strategies, experiments, and system scalability to advance state-of-the-art capabilities in digital finance AI.