About the Role
The role involves building robust evaluation systems for large language models, analyzing model outputs, and translating findings into actionable insights to guide development and deployment.
Responsibilities
- Develop evaluation methodologies tailored to large language model behaviors
- Design experiments to assess model accuracy, coherence, and safety
- Analyze model responses across diverse input conditions
- Collaborate with engineering teams to integrate feedback loops
- Identify edge cases and failure modes in model outputs
- Create metrics to quantify model performance over time
- Produce clear reports summarizing evaluation results
- Work closely with research teams to refine model training objectives
- Ensure evaluations align with ethical and safety standards
- Iterate on testing frameworks based on new model capabilities
Nice to Have
- Master’s or PhD in a relevant technical discipline
- Direct experience evaluating large language models
- Background in cognitive science or linguistics
- Experience with A/B testing frameworks
- Familiarity with model alignment research
- Contributions to open-source NLP projects
- Published work in machine learning or AI conferences
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility
Team
Collaborative team focused on advancing large language model performance
About the Team
- The team focuses on improving the real-world performance of large language models through rigorous testing and analysis.
- Members come from diverse technical and research backgrounds with shared interest in AI reliability.
What We Value
- Rigorous empirical methods
- Clear communication of technical findings
- Commitment to ethical AI development
Available for qualified candidates
