Research Scientist, Recommendation Systems
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The role
Join a cutting-edge research team focused on the next generation of recommendation systems powered by Large Language Models.
Lead exploration of data integration from recommendation domains into foundation models, including data curation, Supervised Fine-Tuning (SFT), and Reinforcement Learning (RL).
Develop and prototype technologies such as Semantic IDs, generative retrieval and ranking, and large user models to demonstrate the art of the possible.
Collaborate closely with product teams to translate research breakthroughs into deployed, scalable solutions for flagship products.
We seek a PhD (or equivalent) with a strong research track record and solid software engineering skills; experience in recommender systems, LLM post-training, and JAX is a plus.
The role emphasizes adaptability, cross-functional collaboration, and driving ideas from conception to production-ready systems.
Lead exploration of data integration from recommendation domains into foundation models, including data curation, Supervised Fine-Tuning (SFT), and Reinforcement Learning (RL).
Develop and prototype technologies such as Semantic IDs, generative retrieval and ranking, and large user models to demonstrate the art of the possible.
Collaborate closely with product teams to translate research breakthroughs into deployed, scalable solutions for flagship products.
We seek a PhD (or equivalent) with a strong research track record and solid software engineering skills; experience in recommender systems, LLM post-training, and JAX is a plus.
The role emphasizes adaptability, cross-functional collaboration, and driving ideas from conception to production-ready systems.
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