Research Engineer / Scientist, Post-training & Reinforcement Learning - London

• Develop and train advanced LLMs and VLMs, including multimodal architectures
• Research and implement training methods for enhanced capabilities like instruction following 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

You have a strong research engineer / scientist mindset with experience training and improving large language models at different scales in distributed computing settings whether that’s modelling, data collection, experimenting and ablating, implementing SOTA.

• You have strong programming skills in Python, Rust, or similar; and strong software engineering fundamentals building performant and reliable systems.
• Proficient in deep learning frameworks (Pytorch, JAX, TensorFlow).
• You can work on different layers of the stack from low-level training backends, data ingestion to ML/RL algorithmic design and implementation.
• You know when and where to be rigorous and slower versus when to break and iterate quickly.
• You have trained LLMs/VLMs with techniques such as SFT, DPO, RLHF/RLVR, reward modelling, offline RL, distillation, etc.

• You have experience with offline and online reinforcement learning in or outside of the context of language models.

• Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV, AAMAS, …)
• Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV)
• Experience with large-scale distributed training and inference (multi-node, large models, MoE, parallelism strategies, etc)
• Experience training models for computer use or other multi-turn and/or multimodal agentic settings.
• Extensive experience with reinforcement learning with sparse rewards.

• Experience with multi-domain training, data mixture design, curriculum learning, model merging, distillation.

• You are a good communicator, collaborative and low-ego.
• You are able to handle a controlled-chaotic environment with a high-degree of between-teams dependencies and collaboration.
• You have a go-do attitude and can balance personal conviction/interests with wider team needs.
• You don’t shy away from hard research or engineering problems.

• Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startups
• Collaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environment.
• Enjoy a highly competitive salary.
• Unlock opportunities for professional growth, continuous learning, and career development

H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential.

H is hiring the world’s best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute.