About the role
Requirements:
- 3-6+ years of experience in ML engineering, data science, model evaluation, ML QA, applied NLP evaluation, or data-heavy quality engineering.
- Strong Python and data analysis skills.
- Strong understanding of precision/recall/F1 calibration, confidence thresholds, dataset splits, leakage, overfitting, statistical testing, and error analysis.
- Experience building evaluation pipelines, benchmark suites, test harnesses, dashboards, or regression frameworks.
- Ability to work with imperfect labels, annotation disagreement, clinical ambiguity, and hidden evaluation sets.
- Strong independence and judgment; ability to challenge releases when evidence is weak.
- Clear written communication for release reports, incident analysis, and quality decisions.