This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a ML Annotation QA Engineer based in India.
As an ML Annotation QA Engineer, you will own the quality and reliability of annotated data supporting computer vision and machine learning systems. You will focus on the judgment-intensive analysis that requires robust technical reasoning and cannot be reliably outsourced. The role combines data analysis, quality assurance, root cause investigation, process design, and cross-functional collaboration with ML and engineering teams. You will build performance tracking systems that reveal patterns across facilities, equipment, data formats, and time. Your findings will help distinguish annotation errors, model regressions, tooling issues, and genuine degradation in real-world environments. Starting with warehouse forklift vision and barcode localization, you will help establish repeatable quality practices that can scale across new AI and robotics programs.
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Accountabilities:




Own the quality analysis of annotated ML and computer vision data that requires in-house judgment, managing daily review queues and producing clear verdicts and root-cause assessments within agreed quality and time thresholds.
Define, maintain, and continuously refine verdict taxonomies, decision rules, quality guidelines, and annotation standards for the data categories under your ownership.
Build and maintain performance trackers that measure error rates across facilities, sites, equipment, and data formats over time against agreed baselines and quality thresholds.
Detect anomalies against established baselines and escalate emerging issues quickly, ensuring problems are investigated while the underlying behavior remains observable.
Conduct root cause analysis on flagged anomalies, distinguishing between annotation errors, model or system failures, tooling issues, and genuine degradation in field performance.
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📌 ML Annotation QA Engineer (India)
🏢 Jobgether
📍 India