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Job Description
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Move to high-performance ML models utilizing factorization for sub-millisecond relevance optimization.
- Build a new pRelevance model that incorporates deep personalization signals through non-traditional techniques like differential modeling and transfer learning.
- Leverage Large Language Model (LLM) based distillation to teach models what is relevant in scenarios where manual dataset creation is unfeasible.
- Develop evaluation frameworks where LLMs simulate user personas to predict true ad quality.