Principal Research Engineer (Post-Training)

Join as a Principal Research Engineer on the Post-Training team. In this highly cross-functional role, you will drive the technical vision and execution of systems that transform foundation models into intelligent and engaging products. You will lead initiatives spanning data, algorithms, infrastructure, and evaluation, and partner closely with researchers, engineers, product teams, and infrastructure teams. Your work will directly shape the conversational experiences of millions of users every day. - Conduire la vision technique, l'exécution et l'évolution des systèmes qui transforment les modèles de base en produits intelligents et engageants. - Diriger le développement d'algorithmes d'alignement, de techniques d'optimisation et d'objectifs d'entraînement pour améliorer les capacités du modèle. - Mentorer et développer une équipe de chercheurs et d'ingénieurs grâce à des conseils techniques, des revues de conception et le développement de carrière. - PhD in Computer Science, Machine Learning, AI, or a related field, or equivalent industry experience - Experience leading teams working on large language model training, mid-training, or post-training - Experience training, serving, debugging, and optimizing large-scale models on GPU-based systems - Strong software engineering skills with the ability to write clean, maintainable, and scalable code - Excellent communication skills and the ability to influence technical direction across teams. Lead complex, cross-functional initiatives across data, training infrastructure, evaluation, and model serving - Experience with product experimentation, online evaluation, and A/B testing frameworks - Expertise in designing, building, and maintaining production-quality ML systems and infrastructure - Deep understanding of modern machine learning techniques, including transformers, reinforcement learning, alignment methods, and large language models - Significant experience leading technical projects or teams in machine learning, AI research, or large-scale distributed systems. Experience scaling and mentoring high-performing research and engineering teams - Strong track record of delivering impactful research or applied ML systems in production environments - Hands-on experience working directly with open-source models like Mistral and Qwen, particularly adapting them via mid- and post-training for specific personas, creative writing, or role-playing applications - Familiarity with cloud-native ML infrastructure, including Kubernetes, Docker, and modern orchestration platforms - Publications in leading machine learning conferences or demonstrated contributions to the broader AI community