Research Engineer / Scientist, Post-training - Paris

The role

This person will develop and train advanced LLMs and VLMs, including multimodal architectures. They will research training methods for instruction following and tool use while designing data pipelines for large-scale distributed training.

What you will do

• 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

Required qualifications

• 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
• 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)
• Excellent communication and presentation skills
• Strong collaboration and teamwork skills
• Passion for AI and problem-solving

Nice to have

• Industry experience
• Experience with LLM training with RL
• Experience with data processing techniques

Benefits

• Competitive salary
• Opportunities for professional growth, continuous learning, and career development

About the company

H exists to push the boundaries of superintelligence with agentic AI. The Models team builds the foundational models that power agentic technology.