AI Research Engineer — Pushing Agentic Models

H Company; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

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.

Qualifications

• Strong research mindset with experience training and improving large language models at different scales in distributed settings.
• Experience with SFT, RLHF/RLVR, reward modelling, offline RL, distillation.
• Proven ability to ship models into agentic AI applications with practical constraints.

Responsibilities

• Develop and train advanced LLMs and VLMs, including multimodal architectures.
• Research and implement training methods for enhanced capabilities and tool use.
• Design and optimize data pipelines and training systems for large-scale distributed training.
• Collaborate with cross-functional teams to integrate models into agentic AI systems.
• Evaluate model performance and communicate findings to stakeholders.
• Stay current with advancements in LLMs, VLMs, and related fields.

Skills

Python

Rust

Deep learning

Pytorch

JAX

TensorFlow

RLHF/RLVR

SFT

Offline RL

Education

PhD or MSc in ML/DL/NLP

Tools

Distributed training infra

MoE architectures

Large-scale data pipelines

Job description

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.