New opportunity

Researcher, Post Training

Cartesia · San Francisco, United States

About this role

Researcher on the Post-Training team developing post-training and alignment methods for multimodal foundation models, designing preference optimization, evaluation frameworks, and feedback-driven learning. The role includes implementing, debugging, and scaling experimental systems and translating research findings into production-ready systems to improve model reasoning and human alignment.

Skills for this role

Preference optimizationAlignment methodsRLHFMultimodal model trainingGenerative modelsModel evaluationMetrics designFeedback-driven learningHuman-in-the-loop evaluationMachine learning systems engineeringModel debuggingScaling ML systemsReproducibility in trainingState Space Models (SSMs)Foundation models