Anthropic’s production models undergo sophisticated post‑training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on the Post‑Training team, you will train our base models through the complete post‑training stack to deliver the production Claude models that users interact with, implementing, scaling, and improving techniques such as Constitutional AI and RLHF.
Research Engineer, Production Model Post-Training at Anthropic
Hybrid - Zürich, CH
More jobs at AnthropicRequirements
Skills
- Strong software engineering skills with experience building complex ML systems
- Experience with large-scale distributed systems and high-performance computing
- Experience with training, fine-tuning, or evaluating large language models
- Proficiency in Python
- Proficiency in deep learning frameworks
- Proficiency in distributed computing
- Bachelor’s degree or equivalent
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
See if your resume is ready for this job
See how our AI can optimize your resume and improve your chances for this role.