Applied ML Evaluation Auditor
Listed on 2026-10-07
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Quality Assurance - QA/QC
Obsidian is seeking an applied ML evaluator to assess the quality, correctness, and rigor of experiments used to train frontier AI models. You will review experiment design, model-selection reasoning, and evaluation methodology.
This role emphasizes data-quality hygiene, leakage detection, and reproducibility—no MLOps duties. Experience with PyTorch, Tensor Flow, scikit-learn, and XGBoost is expected; prior peer review or benchmarking is a plus.
Join us at Obsidian as our next Applied ML Evaluation Auditor in San Francisco, CA, United States.
Join Obsidian and contribute to our ongoing work.
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This posting is for the Applied ML Evaluation Auditor role at Obsidian, based in San Francisco, CA, United States.
We are looking to fill the Applied ML Evaluation Auditor position at Obsidian in San Francisco, CA, United States.
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