AI Research Engineer – Pre-training, LLM, Multi-Modal

🕒 August 10

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 30%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Tether.to

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

₿ Crypto

💳 Fintech

💸 Finance

Crypto • Fintech • Finance

Tether. to is a leading digital asset company that pioneers the use of stablecoins in the blockchain space. As the most widely adopted stablecoin, Tether tokens are designed to be pegged 1-to-1 with fiat currencies, offering a stable digital asset option for users. The platform facilitates these token transactions across multiple blockchains, enhancing cross-border transactions while maintaining transparency with daily records of total assets and reserves. Tether's initiatives include educational programs promoting digital asset usage, especially targeting regions like the Middle East, Turkey, and the Philippines. Tether thus positions itself as a disruptor in the traditional financial system by enabling a stable, efficient method of handling transactions in the digital currency world.

📋 Description

• Conduct foundational pre-training for LLMs and multi-modal models integrating text, vision, audio, or other modalities on large distributed servers with multiple nodes and thousands of NVIDIA GPUs • Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers • Source, filter, and curate large-scale textual and multi-modal datasets and establish robust data pipelines • Execute experiments independently and collaboratively, analyze results, and refine training methodologies for performance and token efficiency • Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs • Advance distributed training systems for scalability and hardware efficiency

🎯 Requirements

• A degree in Computer Science or related field • Ideally PhD in NLP, Machine Learning, or a related field • Solid track record in AI R&D • Good publications in A* conferences • Hands-on experience contributing to large-scale LLM or multi-modal pre-training runs on distributed servers with thousands of NVIDIA GPUs • Familiarity and practical experience with large-scale distributed training frameworks, libraries, and tools • Deep knowledge of state-of-the-art transformer and non-transformer modifications for intelligence, efficiency, and scalability • Strong expertise in PyTorch and Hugging Face libraries • Practical experience in model development, continual pretraining, and deployment • Excellent English communication skills

🏖️ Benefits

• Remote work from every corner of the world • Opportunity to collaborate with a global talent powerhouse • Opportunity to contribute to innovative fintech, blockchain, AI, and digital finance products