AI Forschung Ingenieur (Pre-training - LLM & Multi-Modal) — Tether Operations
NeuCHF 49'500 - 75'000
Tether Operations · Zürich, Zürich (ZH)
- Ort
- Zürich
- Vertrag
- remote
- Veröffentlicht
- vor 3 Tagen
LohnCHF 49'500 - 75'000
Rollenüberblick
Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution.
Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains.
By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost.
- Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution.
- Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains.
- Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs.
- Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding.
Hauptaufgaben
- Large-Scale Pre-Training: Conduct foundational pre-training for LLMs and Multi-Modal models (integrating text, vision, audio, or other modalities) on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs.
- Architecture & Alignment Innovation: Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers to enhance model intelligence and multi-modal understanding.
- Data Strategy: Source, filter, and curate massive-scale textual and multi-modal datasets, establishing robust data pipelines for efficient pre-training.
- Experimental Research: Independently and collaboratively execute experiments, analyze results, and refine training methodologies for optimal performance and token efficiency.
- Optimization & Debugging: Investigate, debug, and eliminate bottlenecks in model efficiency, computational performance, and multi-modal alignment stability during long training runs.
- System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. A degree in Computer Science or related field.
- Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
- Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance.
- 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 aimed at enhancing intelligence, efficiency and scalability.
Bewerbungsprozess
- only through our official channels.
- We do not use third-party platforms or agencies for recruitment unless clearly stated.
- All open roles are listed on our official careers page: https://tether.recruitee.com/
- Verify the recruiter’s identity.
- All our recruiters have verified LinkedIn profiles.
- If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
- Be cautious of unusual communication methods.
- We do not conduct interviews over WhatsApp, Telegram, or SMS.
Kontakte
- Double-check email addresses.
Weitere Details
- System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms. A degree in Computer Science or related field.
- Apply only through our official channels.
Notizen und Originalinhalt
- Responsibilities
- System Scalability: Contribute to the advancement of distributed training systems to ensure seamless scalability and hardware efficiency on target platforms.
- A degree in Computer Science or related field.
