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AI Research Engineer (Pre-training)
Bitfinex
Dubai
On-site
USD 80,000 - 120,000
Full time
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Job summary
A leading fintech company is seeking an AI Research Engineer to drive innovation in AI model architecture and pre-training. The successful candidate will have a strong background in machine learning, particularly in LLM architectures, and will work with large-scale distributed systems to enhance model capabilities. This role offers the opportunity to contribute to cutting-edge solutions and collaborate with top talents in a fast-growing global team.
Qualifications
- Deep expertise in LLM architectures and pre-training optimization.
- Hands-on experience with large-scale LLM training runs.
- Strong expertise in PyTorch and Hugging Face.
Responsibilities
- Conduct pre-training AI models on distributed servers equipped with thousands of NVIDIA GPUs.
- Design and prototype innovative architectures for AI models.
- Analyze results and refine methodologies for optimal performance.
Skills
Education
Tools
Job description
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27.06.2025
11.08.2025
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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 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. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
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Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job:
As a member of the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field.
You will have a deep expertise in LLM architectures, a strong grasp of pre-training optimization with a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: data curation, strengthening baselines, identifying and resolving existing pre-training bottlenecks to push the limits of AI performance.
Responsibilities:
Conduct pre-training AI models on large, distributed servers equipped with thousands of NVIDIA GPUs.
Design, prototype, and scale innovative architectures to enhance model intelligence.
Independently and collaboratively execute experiments, analyze results, and refine methodologies for optimal performance.
Investigate, debug, and improve both model efficiency and computational performance.
Contribute to the advancement of training systems to ensure seamless scalability and 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 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.
Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment.
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