AI Research Engineer (Fine-tuning)

Tether; Ireland; Remote; EUR 70,000 - 120,000; Full time

Job summary

Join Tether, a leader in digital finance, as part of the AI model team. You'll innovate in fine-tuning methodologies for advanced models, improving performance and capabilities for real-world applications. This role demands expertise in large language models, strong hands-on experience with PyTorch, and a passion for AI R&D, with competitive compensation aligned with Fintech standards.

Qualifications

• A strong record in AI R&D with publications in top conferences.
• Hands-on experience with large-scale fine-tuning.
• Ability to design evaluation frameworks and iterate on improvements.

Responsibilities

• Develop and implement fine-tuning methodologies with performance targets.
• Conduct controlled experiments and track performance against benchmarks.
• Collaborate with teams to deploy models into production and monitor improvements.

Skills

Transformer architectures

Fine-tuning techniques

PyTorch

Hugging Face libraries

Dataset curation

Education

Degree in Computer Science or related field

PhD in NLP or Machine Learning

Job description

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 enable seamless integration of reserve-backed tokens across blockchains, empowering businesses such as exchanges, wallets, payment processors, and ATMs. Using blockchain technology, Tether allows users to store, send, and receive digital tokens instantly, securely, and globally at a low cost. Transparency is fundamental to our operations, fostering trust in every transaction.

Innovate with Tether

Tether Finance: Our product suite features the trusted stablecoin USDT, used by hundreds of millions worldwide, along with innovative digital asset tokenization services.

Additional initiatives include:

• Tether Power: Eco-friendly energy solutions optimizing excess power for Bitcoin mining in geo-diverse facilities.
• Tether Data: Enhancing AI and peer-to-peer tech with solutions like KEET, our secure data sharing app.
• Tether Education: Providing digital learning access to empower individuals in the digital and gig economies.
• Tether Evolution: Merging technology and human potential to push innovation and expand possibilities.

Why Join Us?

Our global, remote team is passionate about fintech innovation. Join us to collaborate with top talent, push industry boundaries, and set new standards. We are fast-growing, lean, and industry leaders.

If you have excellent English communication skills and want to contribute to one of the most innovative platforms, Tether is your destination.

Are you ready to be part of the future?

About the job:

As a member of our AI model team, you will innovate in supervised fine-tuning methodologies for advanced models, refining pre-trained models to improve intelligence, performance, and domain-specific capabilities for real-world applications. Your work will span from resource-efficient models to complex multi-modal architectures involving text, images, and audio.

We seek expertise in large language model architectures and extensive experience in fine-tuning optimization. Your role involves developing, testing, and deploying new techniques, curating domain-specific data, and resolving bottlenecks to unlock superior AI performance.

Responsibilities:

• Develop and implement novel fine-tuning methodologies with performance targets.
• Conduct controlled experiments, track performance, document results, and compare against benchmarks.
• Curate high-quality, domain-specific datasets with measurable impact on model performance.
• Analyze and optimize the fine-tuning process through performance metrics.
• Collaborate with teams to deploy models into production, defining success metrics and monitoring improvements.

Minimum qualifications:

• A degree in Computer Science or related field; PhD in NLP, Machine Learning, or similar is preferred, with a strong record in AI R&D and publications in top conferences.
• Hands-on experience with large-scale fine-tuning, demonstrating measurable improvements.
• Deep knowledge of transformer architectures and advanced fine-tuning techniques to enhance model efficiency and scalability.
• Proficiency in PyTorch and Hugging Face libraries, with practical experience deploying models in production.
• Ability to apply empirical research to overcome fine-tuning challenges, designing evaluation frameworks and iterating on improvements.