Responsibilities
- Design and implement novel data curation pipelines to identify, verify, and filter training data for accuracy given the model’s knowledge
- Develop specialized classifiers to detect potential hallucinations or miscalibrated claims made by the model
- Create and maintain comprehensive honesty benchmarks and evaluation frameworks
- Implement techniques to ground model outputs in verified information, such as search and retrieval-augmented generation (RAG) systems
- Design and deploy human feedback collection specifically for identifying and correcting miscalibrated responses
- Design and implement prompting pipelines to generate data that improves model accuracy and honesty
- Develop and test novel RL environments that reward truthful outputs and penalize fabricated claims
- Create tools to help human evaluators efficiently assess model outputs for accuracy
Work Arrangement
Remote (City/Region)
Additional Information
- All interviews in Python
- We have filled our headcount for 2025. However, we are leaving this form open as an expression of interest since we expect to be growing the team in the future, and we will review your application when we do. As such, you may not hear back on your application to this team until the new year
