Applied ML Evaluation Auditor
Listed on 2026-09-17
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Quality Assurance - QA/QC
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IT/Tech
Data Scientist
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.
Are you ready to take on the Applied ML Evaluation Auditor role at Obsidian?
All applications are reviewed carefully by our team.
This is a Full Time role.
The position is based in San Francisco, CA, United States.
This opportunity is part of our work in IT & Technology.
The advertised compensation is 90..
We aim to respond to suitable candidates as soon as possible.
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