Research Engineer, Production Model Post-Training en Anthropic

Híbrido - Zürich, CH

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Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

Requirements

Skills

  • Strong software engineering skills with experience building complex ML systems
  • Comfortable working with large-scale distributed systems and high-performance computing
  • Experience with training, fine-tuning, or evaluating large language models
  • Proficiency in Python, deep learning frameworks, and distributed computing
  • Experience with LLMs
  • Keen interest in AI safety and responsible deployment
  • Ability to balance research exploration with engineering rigor and operational reliability
  • Adept at analyzing and debugging model training processes
  • Excellent collaboration across research and engineering disciplines
  • Adaptability to changing priorities and ambiguity

Responsibilities

  • Implement and optimize post-training techniques at scale on frontier models
  • Conduct research to develop and optimize post-training recipes that directly 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
  • Debug complex issues in training pipelines and model behavior
  • Help establish best practices for reliable, reproducible model post-training

Technologies

PythonDeep learning frameworksDistributed computingConstitutional AIRLHF

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