Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and deploy AI models across various devices using cutting-edge technologies.
- Company: Tether is revolutionising digital finance with innovative solutions and a global remote team.
- Benefits: Enjoy remote work flexibility, collaborative culture, and opportunities for professional growth.
- Why this job: Be part of a passionate team shaping the future of fintech and AI technology.
- Qualifications: Proficient in Python, C, C++, with experience in Llama.cpp and ggml; degree in Computer Science or related field.
- Other info: Join us to lead the industry with advanced AI models and make a real impact.
The predicted salary is between 48000 - 72000 £ per year.
Senior AI Engineer (ggml/llama.cpp Specialist)
Senior AI Engineer (ggml/llama.cpp Specialist)
Tether Operations Limited – London, United Kingdom
Join Tether and Shape the Future of Digital Finance
At Tether, we\’re pioneering a global financial revolution with cutting-edge solutions that enable seamless, secure, and instant digital transactions across blockchains. Our products include the trusted stablecoin USDT, energy-efficient Bitcoin mining solutions, innovative AI and data sharing platforms, and educational initiatives to democratize digital learning.
Why Join Us?
Our remote, global team is passionate about fintech innovation. If you have excellent English communication skills and want to make a mark in the industry, Tether offers a collaborative environment to grow and innovate.
About the job:
This role involves building versatile AI models for deployment on a range of devices, from edge devices like smartphones to large-scale systems, using GGML as the core inference backend. Join us in developing AI solutions that surpass current industry standards.
Responsibilities:
- Deploy machine learning models on edge devices using llama.cpp, ggml, and onnx frameworks.
- Collaborate with research teams to code, train, and transition models from research to production.
- Integrate AI features into existing products with the latest machine learning advancements.
Minimum Requirements:
- Proficiency in Python, C, and C++ programming.
- Experience with Llama.cpp and ggml inference engines, especially for GPU deployment.
- Understanding of deep learning, transformers, and LLMs.
- Ability to quickly learn new technologies.
- Degree in Computer Science, AI, or related field, with a strong AI R&D background.
Join us in building advanced AI models that lead the industry forward.
#J-18808-Ljbffr
Senior AI Engineer (ggml/llama.cpp Specialist) | London, UK employer: Tether Operations Limited
Contact Detail:
Tether Operations Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer (ggml/llama.cpp Specialist) | London, UK
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly focusing on ggml and llama.cpp. This will not only help you understand the technical requirements but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the fintech and AI sectors. Attend relevant meetups or webinars where you can connect with current employees at Tether or similar companies. This could provide you with insider knowledge and potentially a referral.
✨Tip Number 3
Showcase your practical experience by working on personal projects that involve deploying AI models on edge devices. Having a portfolio of such projects can demonstrate your hands-on skills and passion for the field.
✨Tip Number 4
Prepare for technical interviews by brushing up on your coding skills in Python, C, and C++. Practice solving problems related to AI model deployment and optimisation, as these are likely to come up during the interview process.
We think you need these skills to ace Senior AI Engineer (ggml/llama.cpp Specialist) | London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, C, and C++, as well as your familiarity with ggml and llama.cpp. Emphasise any projects or roles where you've deployed machine learning models, particularly on edge devices.
Craft a Compelling Cover Letter: In your cover letter, express your passion for fintech innovation and how your skills align with Tether's mission. Mention specific experiences that demonstrate your ability to collaborate with research teams and transition models from research to production.
Showcase Relevant Projects: If you have worked on relevant AI projects, include them in your application. Detail your role, the technologies used (like ggml and llama.cpp), and the impact of your work. This will help illustrate your hands-on experience.
Highlight Continuous Learning: Tether values the ability to quickly learn new technologies. In your application, mention any recent courses, certifications, or self-study efforts related to AI, deep learning, or machine learning frameworks that showcase your commitment to professional growth.
How to prepare for a job interview at Tether Operations Limited
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python, C, and C++. Highlight specific projects where you've used Llama.cpp and ggml, especially in GPU deployment. This will demonstrate your hands-on experience and technical expertise.
✨Understand the Company’s Vision
Familiarise yourself with Tether's mission in digital finance and their innovative products. Being able to articulate how your skills align with their goals will show your genuine interest in the role and the company.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges or case studies during the interview. Practice explaining your thought process clearly and logically, as this will showcase your problem-solving abilities and understanding of AI model deployment.
✨Demonstrate Collaborative Spirit
Since the role involves collaboration with research teams, be ready to discuss your experiences working in teams. Share examples of how you’ve successfully integrated AI features into existing products and how you handle feedback and suggestions.
