Applied ML Task Auditor — Experiment Quality Lead

Dorado; Northern (KY); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Dorado is seeking a specialist to evaluate the quality, correctness, and methodological rigor of applied ML tasks used to train and evaluate frontier AI lab models. You will assess experiment design, model-selection reasoning, and evaluation methodology, and provide rubric-based written feedback.

The role emphasizes critical appraisal of ML claims, dataset quality, and reproducibility, with no focus on LLM deployment or MLOps.

Qualifications

• 3+ years hands-on applied ML experience including experiment design, model selection, and evaluation.
• Strong data-quality rigor including leakage detection, metric gaming, and train/test/CV hygiene.
• Proficiency with standard ML frameworks: PyTorch, TensorFlow, scikit-learn, XGBoost.
• Ability to critique ML claims against evidence and reproduce results.

Skills

Hands-on ML experience

Experiment design

Model selection reasoning

Evaluation methodology

Reproducing results

Critiquing ML claims

Tools

PyTorch

TensorFlow

scikit-learn

XGBoost

Job description

Dorado is seeking a specialist to evaluate the quality, correctness, and methodological rigor of applied ML tasks used to train and evaluate frontier AI lab models. You will assess experiment design, model-selection reasoning, and evaluation methodology, and provide rubric-based written feedback.

The role emphasizes critical appraisal of ML claims, dataset quality, and reproducibility, with no focus on LLM deployment or MLOps.