AI Research Engineer β€” Pushing Agentic Models in London

AI Research Engineer β€” Pushing Agentic Models in London

London Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
H

At a Glance

  • Tasks: Lead research and engineering to advance agentic AI with cutting-edge models.
  • Company: Join a pioneering company at the forefront of AI innovation.
  • Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
  • Other info: Dynamic hybrid work culture between London and Paris.
  • Why this job: Make a real impact in AI by working on groundbreaking projects.
  • Qualifications: Experience in AI research, data pipelines, and collaborative teamwork.

The predicted salary is between 80000 - 100000 Β£ per year.

H is hiring to advance agentic AI by building and refining large language and vision-language models.

You will lead research and engineering efforts across data pipelines, backends, and multi-node distributed training to push capabilities in complex environments.

The role emphasizes SFT, RLHF/RLVR and reward modelling, with a focus on practical deployment and cross-functional collaboration in a hybrid London/Paris setting.

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AI Research Engineer β€” Pushing Agentic Models in London employer: H Company

H Company is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the fast-paced AI sector. With a strong emphasis on employee growth, you will have access to cutting-edge projects and the opportunity to work alongside talented professionals in either Paris or London, all while enjoying the flexibility of a hybrid work model. Join us to be part of a mission-driven team that values your contributions and supports your professional development.

H

Contact Details:

H Company Recruitment Team

We think you need these skills to ace AI Research Engineer β€” Pushing Agentic Models in London

Large Language Models
Vision-Language Models
Data Pipelines
Backend Development
Multi-Node Distributed Training
SFT (Supervised Fine-Tuning)
RLHF (Reinforcement Learning from Human Feedback)