About this opportunity
Confidential lists this Machine Learning Task Auditor opportunity in West Lake Hills, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Role Overview Help strengthen the applied machine-learning tasks used to train and evaluate models at a frontier AI lab. You will assess task quality, correctness, and methodological rigor, with particular attention to experiment design, model-selection rationale, and evaluation methods. This is an applied and experimental ML evaluation role, not an LLM application development or MLOps position.
Key Responsibilities Review applied machine-learning tasks for quality, correctness, and methodological soundness.
Evaluate experiment design, model-selection reasoning, and evaluation methodology.
Provide clear, written feedback using established rubrics.
Assess ML claims against available evidence and reproduce results when needed.
Qualifications At least 3 years of hands-on applied or experimental machine-learning experience, including experiment design, model selection, hyperparameter tuning, and evaluation methodology.
Strong data-quality rigor, including leakage detection, metric gaming, and appropriate train, test, and cross-validation practices.
Proficiency with standard ML frameworks, including PyTorch, TensorFlow, scikit-learn, and XGBoost.
Ability to critically evaluate machine-learning claims using evidence and reproduce results.
Preferred Qualifications Competition or benchmark experience, such as Kaggle.
Graduate research experience or a publication record in applied machine learning.
Previous task-grading or peer-review experience.
Work Terms Remote role open to candidates located in the United States.
Hourly employment arrangement.
Compensation $70 to $90 per hour.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.