Researcher, Training - London

Researcher, Training - London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
United States Digital Space LLC

At a Glance

  • Tasks: Design and enhance cutting-edge language models to push the boundaries of AI.
  • Company: Join a leading tech company focused on advancing artificial general intelligence.
  • Benefits: Competitive salary, relocation support, hybrid work schedule, and a collaborative environment.
  • Other info: On-site role in London with excellent career growth opportunities.
  • Why this job: Be at the forefront of AI development and make a real impact in the tech world.
  • Qualifications: Experience with LLM training and a passion for innovative AI solutions.

The predicted salary is between 60000 - 80000 £ per year.

About the Team

The company'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 the company'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.

Responsibilities

  • 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

Qualifications

  • Experience landing contributions to major LLM training runs
  • Ability to thoroughly evaluate and improve deep learning architectures in a self‑directed fashion
  • Motivation for safely deploying LLMs in the real world
  • Well‑versed in state‑of‑the‑art transformer modifications for efficiency

Workplace & Location

This role is based in London, and we require on‑site presence; remote work is not an option. We offer relocation support and a hybrid schedule of three days a week in the office, with option to work from home on Thursdays and Fridays.

Equal Opportunity

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 legally protected characteristic.

Researcher, Training - London employer: United States Digital Space LLC

As a leading innovator in the field of artificial intelligence, our company offers an exceptional work environment for researchers in London, where collaboration and creativity are at the forefront of our mission to advance large language models. With a strong emphasis on employee growth, we provide opportunities for professional development, a supportive culture that values diverse perspectives, and a hybrid work schedule that promotes work-life balance. Join us to be part of a team that is not only pushing the boundaries of technology but also committed to making a meaningful impact in the world.

United States Digital Space LLC

Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

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We think you need these skills to ace Researcher, Training - London

Deep Learning
Large Language Models (LLMs)
Architecture Design
Model Inference
Experiment Analysis
Debugging
Optimization Techniques

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