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About
Design and write detailed evaluation suites for machine learning engineering tasks. Assess AI generated solutions across model training, debugging, optimization, and experimentation. Translate real world ML workflows into structured benchmarks for frontier models. Apply strong technical judgment to evaluate ML system design choices and tradeoffs. Work independently within a research driven, asynchronous project environment. Requirements
Strong experience in machine learning engineering or applied ML research. Hands on experience with model development, experimentation, and evaluation. Background in ML research in industry or academic settings preferred. Strong written communication skills and high attention to technical detail. Ability to work independently and deliver high quality outputs on short timelines.
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Languages
- English
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