Staff AI Scientist - LLMs, RL & Long-Context Equity London

Staff AI Scientist - LLMs, RL & Long-Context Equity London

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Enigma

At a Glance

  • Tasks: Own AI projects end-to-end, focusing on LLMs and reinforcement learning.
  • Company: Fast-growing AI startup in London with a dynamic team.
  • Benefits: Competitive salary, equity, and a collaborative work environment.
  • Other info: Flat structure promoting autonomy and rapid learning.
  • Why this job: Join an ambitious team and make a real impact in AI innovation.
  • Qualifications: Experience in AI, LLMs, and a passion for experimentation.

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

Enigma in London is seeking a Member of Technical Staff to own projects end-to-end across large language models, reinforcement learning, post-training work, and long-context reasoning, contributing across multiple initiatives in a fast-growing AI startup. You will work with a small, ambitious team, learn quickly, and operate with high ownership in a flat, autonomous environment.

The role offers a competitive salary and equity, with a strong emphasis on collaboration and experimentation.

Staff AI Scientist - LLMs, RL & Long-Context Equity London employer: Enigma

Enigma is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong focus on employee growth, we provide ample opportunities for professional development and hands-on experience in cutting-edge technologies within the healthcare sector. Our commitment to reliability, security, and privacy compliance ensures that you will be part of a meaningful mission, making a real impact on clinical monitoring and patient care.

Enigma

Contact Details:

Enigma Recruitment Team

We think you need these skills to ace Staff AI Scientist - LLMs, RL & Long-Context Equity London

Python
Communication Skills
SQL
Data Engineering
Attention to Detail
Problem-Solving Skills
ETL/ELT Processes