AI Research Engineer (Pre-training - LLM & Multi-Modal) - 100% Remote Worldwide
Tether Operations Limited3 months ago
Remote, WorldwideSenior
Responsibilities
- Conduct foundational pre-training for LLMs and multi-modal models using large distributed systems with thousands of NVIDIA GPUs.
- Design, prototype, and scale model architectures, tokenizers, and cross-modal alignment layers.
- Source, filter, and curate large textual and multi-modal datasets and build efficient data pipelines.
- Execute experiments, analyze results, and refine training methods for model performance and token efficiency.
- Investigate and resolve model-efficiency, computational-performance, and multi-modal-alignment bottlenecks during long training runs.
- Advance distributed training systems for scalability and hardware efficiency.
Requirements
- Bachelor's degree in Computer Science or a related field.
- PhD in NLP, Machine Learning, or a related field is preferred.
- A strong track record in AI research and development, ideally including publications at A* conferences.
- Hands-on experience contributing to large-scale LLM or multi-modal pre-training runs on distributed systems 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, including practical experience in model development, continual pre-training, and deployment.
- Excellent English communication skills.
Benefits
- 100% remote worldwide work arrangement.
- Opportunity to collaborate with a global team on cutting-edge AI and digital-finance initiatives.
Tech Stack
Categories
AI ResearchML Engineering
About Tether Operations Limited
Tether Operations Limited develops and issues reserve-backed digital tokens used by exchanges, wallets, payment processors, and merchants, most notably the USDT stablecoin available across multiple blockchains. Founded in 2014 and privately held, it earns revenue from token issuance, reserve management, and related services, and has expanded into tokenization, peer-to-peer communications (Keet), and Bitcoin mining. USDT is widely used in crypto trading and cross-border transfers, including in emerging markets.