Research Engineer / Scientist, Post-training - London

Responsibilities

• 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

Requirements

• Technical skills:
• Strong programming skills (Python, Git)
• Expertise in deep learning frameworks (PyTorch, JAX, TensorFlow)
• Experience with large-scale distributed training of LLMs and VLMs
• Hands-on experience with LLM training, alignment, and reinforcement learning
• Knowledge of multimodal architectures and applications
• Research skills:
• Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV)
• Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV)
• Soft skills:
• Excellent communication and presentation skills
• Strong collaboration and teamwork skills
• Passion for AI and problem-solving
• Bonuses:
• Industry experience
• Experience in LLM training with RL
• Experience with data processing techniques
• Location:
• Paris or London.
• This role is hybrid, and you are expected to be in the office 3 days a week on average.
• Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks).

Benefits

Additional Information

About H: 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. About the Team: The Models team builds the foundational models that power our cutting-edge agentic technology. We focus on training techniques to optimize model capabilities specifically for agent applications. This allows us to achieve the best performance at a given inference cost. Our work spans the development of Large Language Models (LLMs) and Vision-Language Models (VLMs), enabling agents to perceive, understand, and act within complex environments. We are deeply involved in enhancing these models through training methods with a focus on improved instruction following, tool use, and interaction with dynamic environments via large-scale reinforcement learning and reward modeling. We operate at the intersection of research and product, translating cutting-edge research into practical solutions that drive the next generation of AI. We are looking for bright, motivated individuals to join our ranks and shape the future of superintelligent AI.

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