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- Tasks: Drive innovation in fine-tuning AI models for enhanced performance and intelligence.
- Company: Join Tether, a leader in digital finance, pioneering blockchain solutions globally.
- Benefits: Enjoy remote work flexibility and collaborate with top talent worldwide.
- Why this job: Be part of a fintech revolution, pushing boundaries in AI and technology.
- Qualifications: Degree in Computer Science; PhD preferred, with expertise in AI R&D and fine-tuning.
- Other info: Hands-on experience with PyTorch and Hugging Face is essential.
The predicted salary is between 36000 - 60000 £ per year.
Join Tether and shape the future of digital finance. At Tether, we're pioneering a global financial revolution with cutting-edge solutions that empower businesses to seamlessly integrate reserve-backed tokens across blockchains. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
As a member of the AI model team, you will drive innovation in supervised fine-tuning methodologies for advanced models. Your work will refine pre-trained models to deliver enhanced intelligence, optimized performance, and domain-specific capabilities designed for real-world challenges. You will work on a wide spectrum of systems, from streamlined, resource-efficient models to complex multi-modal architectures that integrate data such as text, images, and audio.
We expect you to have deep expertise in large language model architectures and substantial experience in fine-tuning optimization. You will adopt a hands-on, research-driven approach to developing, testing, and implementing new fine-tuning techniques and algorithms. Your responsibilities include:
- Developing and implementing new state-of-the-art fine-tuning methodologies for pre-trained models with clear performance targets.
- Building, running, and monitoring controlled fine-tuning experiments while tracking key performance indicators.
- Identifying and processing high-quality datasets tailored to specific domains.
- Systematically debugging and optimizing the fine-tuning process by analyzing computational and model performance metrics.
- Collaborating with cross-functional teams to deploy fine-tuned models into production pipelines.
Requirements:
- A degree in Computer Science or related field; ideally a PhD in NLP, Machine Learning, or a related field.
- Hands-on experience with large-scale fine-tuning experiments.
- Deep understanding of advanced fine-tuning methodologies.
- Strong expertise in PyTorch and Hugging Face libraries.
- Demonstrated ability to apply empirical research to overcome fine-tuning bottlenecks.
AI Research Engineer (Fine-tuning) employer: Tether Operations Limited
Contact Detail:
Tether Operations Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research Engineer (Fine-tuning)
✨Tip Number 1
Familiarise yourself with the latest advancements in fine-tuning methodologies and large language models. Being well-versed in current trends will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the AI community by attending relevant webinars, conferences, or meetups. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for positions like the one at Tether.
✨Tip Number 3
Showcase your hands-on experience with PyTorch and Hugging Face through personal projects or contributions to open-source initiatives. This practical experience can set you apart from other candidates and highlight your ability to apply theoretical knowledge.
✨Tip Number 4
Prepare to discuss specific challenges you've faced in fine-tuning processes and how you overcame them. Being able to articulate your problem-solving skills will demonstrate your capability to handle real-world challenges in the role.
We think you need these skills to ace AI Research Engineer (Fine-tuning)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI research, particularly in fine-tuning methodologies and large language models. Use specific examples of projects or contributions that demonstrate your expertise in this area.
Craft a Compelling Cover Letter: In your cover letter, express your passion for fintech and how your skills align with Tether's mission. Mention specific projects or achievements that showcase your ability to innovate in AI and your understanding of the challenges in fine-tuning models.
Showcase Your Technical Skills: Clearly outline your proficiency in PyTorch and Hugging Face libraries. Provide examples of how you've developed fine-tuning pipelines and improved model performance in previous roles or projects.
Highlight Collaborative Experience: Tether values teamwork, so be sure to mention any cross-functional collaborations you've been part of. Describe how you worked with other teams to deploy models or improve processes, showcasing your ability to communicate effectively in a remote environment.
How to prepare for a job interview at Tether Operations Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with large language models and fine-tuning methodologies. Highlight specific projects where you've implemented advanced techniques, and be ready to explain the impact of your work on model performance.
✨Demonstrate Problem-Solving Skills
Tether values innovation, so come equipped with examples of how you've identified and resolved bottlenecks in previous projects. Discuss your approach to debugging and optimising fine-tuning processes, showcasing your analytical skills.
✨Familiarise Yourself with Tether's Products
Research Tether's product suite, especially their AI and data solutions. Understanding how your role as an AI Research Engineer fits into their mission will help you articulate your enthusiasm for the position and how you can contribute.
✨Prepare for Collaborative Discussions
Since collaboration is key at Tether, think about how you've worked with cross-functional teams in the past. Be ready to share experiences that demonstrate your ability to communicate effectively and contribute to team success.
