Tech Stack

Description

In this role, you will train Anthropic's base models through the complete post-training stack to deliver production Claude models. You'll work at the intersection of research and engineering, implementing and scaling alignment techniques like Constitutional AI and RLHF, directly impacting model quality and safety.

Requirements

• Strong software engineering skills with experience building complex ML systems
• Experience with training, fine-tuning, or evaluating large language models
• Comfortable working with large-scale distributed systems and high-performance computing
• Proficiency in Python, deep learning frameworks, and distributed computing
• Ability to navigate ambiguity and make progress in fast-moving research environments

Responsibilities

• Implement and optimize post-training techniques at scale on frontier models
• Conduct research to develop and optimize post-training recipes that improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations