ML Engineer

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.