At a Glance
- Tasks: Drive innovation in AI model architecture and enhance multi-modal systems.
- Company: Join Tether, a leader in the fintech revolution with a global remote team.
- Benefits: Work remotely, collaborate with top minds, and shape the future of digital finance.
- Other info: Dynamic environment with opportunities for groundbreaking research and career growth.
- Why this job: Be at the forefront of AI advancements and make a real impact in fintech.
- Qualifications: Degree in Computer Science or related field; experience in AI R&D and large-scale pre-training.
The predicted salary is between 40500 - 49500 £ 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.
Our innovative product suite features the world’s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
Tether is driving sustainable growth with energy solutions that optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art facilities.
We are fueling breakthroughs in AI and peer-to-peer technology, reducing infrastructure costs and enhancing global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
We democratise access to top-tier digital learning, empowering individuals to thrive in the digital and gig economies.
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 deep expertise in Large Language Model (LLM) and Multi-Modal architectures, a strong grasp of pre-training optimization, and a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements.
Responsibilities:
- Conduct foundational pre-training for LLMs and Multi-Modal models on large, distributed servers equipped with multi-nodes & thousands of NVIDIA GPUs.
- Design, prototype, and scale innovative architectures, tokenizers, and cross-modal alignment layers.
- Source, filter, and curate massive-scale textual and multi-modal datasets.
- Independently and collaboratively execute experiments, analyze results, and refine training methodologies.
- Investigate, debug, and eliminate bottlenecks in model efficiency and performance.
- Contribute to the advancement of distributed training systems to ensure seamless scalability.
A degree in Computer Science or related field is required, ideally a PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D.
Hands-on experience contributing to large-scale LLM or Multi-Modal pre-training runs on large, distributed servers is essential.
Familiarity with large-scale, distributed training frameworks, libraries, and tools is necessary.
Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency, and scalability is required.
Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment is expected.
AI Research Engineer (Pre-training - LLM & Multi-Modal) in London employer: Tether
Tether is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for an Edge AI Inference Engineer. With a strong emphasis on employee growth, Tether offers numerous opportunities for professional development and encourages team members to push the boundaries of AI technology in a supportive environment. Located in a vibrant tech hub, employees benefit from a dynamic work atmosphere and access to cutting-edge resources, ensuring that your contributions have a meaningful impact on real-world applications.
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Engineer (Pre-training - LLM & Multi-Modal) in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Tether or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Tether.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Tether.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Tether that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Research Engineer (Pre-training - LLM & Multi-Modal) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Tether.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Tether and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Tether
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Tether uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
