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A leading fintech company in Barcelona is seeking an innovative AI engineer to work on architecture development for AI models. This role requires expertise in LLM architectures and pre-training optimization. Candidates should hold a degree in Computer Science or a related field, preferably a PhD, and have practical experience with large-scale distributed training. The company offers a chance to join a passionate remote team dedicated to fintech innovation.
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Tether Operations Limited
Barcelona, Spain
Other
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Yes
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916192518958638694432460
1
23.07.2025
06.09.2025
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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 solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, at a fraction of the cost. Transparency is our foundation, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our product suite features the trusted stablecoin USDT and digital asset tokenization services.
Additional initiatives include:
Why Join Us?
Our global remote team is passionate about fintech innovation. Join us to work with top talent, set new standards, and contribute to a leading industry platform. Excellent English communication skills are essential.
Are you ready to be part of the future?
About the job:
As part of the AI model team, you will innovate in architecture development for models of various scales, including small, large, and multi-modal systems, enhancing AI capabilities and efficiency.
Your expertise in LLM architectures and pre-training optimization will drive research and implementation of novel techniques, addressing bottlenecks and pushing AI performance limits.
Responsibilities:
Qualifications include a degree in Computer Science or related fields, preferably a PhD in NLP or Machine Learning, with a strong publication record. Practical experience with large-scale distributed training, PyTorch, Hugging Face, and transformer models is required.