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Job Description
- Define and execute the long-term strategy for foundation recommender model pre-training, encompassing both model architecture evolution and future training methodologies.
- Drive a high-velocity research agenda focused on model quality, prioritizing experiments based on compute capacity and researcher bandwidth.
- Partner with ML infrastructure teams to architect training frameworks and ensure the technical ecosystem supports the research and release roadmap.
- Collaborate with data teams to plan data collection for pre-training, setting the standards for data quality to meet foundational model objectives.
- Establish evaluation benchmarks and maintain engaged leaderboards to track progress against baselines and ensure performance.