Machine Learning Engineer II, LLM Applied Science
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The role
Advance LLMs and generative AI through research that can be applied to real-world problems across growth, discovery, ads, and search.
Collect, analyze, and synthesize data to translate research insights into practical, scalable solutions.
Curate and generate training data with strong quality controls and build robust evaluation strategies (offline metrics, human evaluation, red-teaming, robustness & safety).
Write clean, efficient code and collaborate with engineering to land research into production-ready systems.
Develop LLM-powered methods to tackle modeling and ranking challenges across growth and discovery workflows.
Scope and independently solve moderately complex problems while advancing instruction tuning, RAG, tool-calling, and prompt/model optimization.
Collect, analyze, and synthesize data to translate research insights into practical, scalable solutions.
Curate and generate training data with strong quality controls and build robust evaluation strategies (offline metrics, human evaluation, red-teaming, robustness & safety).
Write clean, efficient code and collaborate with engineering to land research into production-ready systems.
Develop LLM-powered methods to tackle modeling and ranking challenges across growth and discovery workflows.
Scope and independently solve moderately complex problems while advancing instruction tuning, RAG, tool-calling, and prompt/model optimization.
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