At a Glance
- Tasks: Design and scale new architectures to enhance AI model intelligence and efficiency.
- Company: Join OpenAI's innovative Training team in London, pushing the boundaries of AI development.
- Benefits: Hybrid work model, relocation support, and a vibrant office environment.
- Other info: Dynamic workplace with focus on collaboration and creativity.
- Why this job: Make a real impact on cutting-edge AI technology and contribute to the future of AGI.
- Qualifications: Experience with LLM training and deep learning architectures is essential.
The predicted salary is between 60000 - 80000 £ per year.
OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture and optimization techniques, alongside long‑term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world‑class in every respect.
About the Role
As a member of the training team, you will push the frontier of LLM development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Relevant interests may include areas such as architecture design, long‑context and efficient attention, optimization and the science of scaling. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands‑on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck.
In this role, you will:
- Design, prototype and scale up new architectures to improve model intelligence.
- Execute and analyze experiments autonomously and collaboratively.
- Study, debug, and optimize both model performance and computational performance.
- Contribute to training and inference infrastructure.
You might thrive in this role if you:
- Have experience landing contributions to major LLM training runs.
- Can thoroughly evaluate and improve deep learning architectures in a self‑directed fashion.
- Are motivated by safely deploying LLMs in the real world.
- Are well‑versed in the state‑of‑the‑art transformer modifications for efficiency.
Workplace & Location: This role is based in our London office, and we aren’t considering applications to work remotely at this time. If you're joining us in person, we offer relocation support and follow a hybrid schedule: three days a week in the office, with the option to work from home on Thursdays and Fridays. Our offices are set up for focus and connection—with adjustable desks, phone booths, conference rooms, stocked kitchens, and cozy spots to unwind or catch up with teammates.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
Researcher, Training - London employer: OpenAI
OpenAI is an exceptional employer, offering a dynamic work environment in London where innovation thrives. With a strong focus on employee growth, we provide opportunities to engage in cutting-edge research and development of large language models, alongside a supportive hybrid work model that promotes work-life balance. Our modern office is designed for collaboration and creativity, ensuring that every team member can contribute meaningfully to our mission of advancing artificial general intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Researcher, Training - London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at OpenAI. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! If you’ve got projects or research that align with LLMs, make sure to showcase them. Whether it’s on GitHub or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for interviews by diving deep into the latest trends in LLM architecture and optimisation techniques. We want to see your passion and knowledge shine through when discussing your ideas and experiences.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Researcher, Training - London
Some tips for your application 🫡
Show Your Passion for LLMs:When writing your application, let your enthusiasm for large language models shine through. We want to see that you’re not just knowledgeable but genuinely excited about pushing the boundaries of AI technology.
Tailor Your Experience:Make sure to highlight relevant experiences that align with the role. Whether it’s your hands-on work with model architectures or your knack for debugging, we want to see how your background fits into our mission.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Remember, we’re looking for someone who can communicate complex ideas effectively!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at OpenAI
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models and their architectures. Be ready to discuss specific examples of how you've contributed to LLM training runs or optimised model performance in the past. This shows you're not just familiar with the theory but have practical experience too.
✨Show Your Problem-Solving Skills
Prepare to talk about times when you've debugged complex issues or tracked down performance bottlenecks. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it clear how your hands-on approach led to successful outcomes.
✨Be Ready for Technical Questions
Expect some deep technical questions related to architecture design and optimisation techniques. Brush up on state-of-the-art transformer modifications and be prepared to explain how they can improve efficiency. This is your chance to showcase your sophisticated understanding of model inference.
✨Demonstrate Your Collaborative Spirit
Since the role involves both autonomous and collaborative work, be ready to discuss how you've successfully worked in teams. Share examples of how you’ve executed experiments with others and contributed to a positive team dynamic, as this will highlight your ability to thrive in a hybrid work environment.
