ML Annotation QA Engineer

New

JobgetherWarehouse Automation/AI

IndiaFull-TimeMiddle

Salary not disclosed

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Job Details

Experience: 2–5 years
Required Skills: PythonSQLData AnalysisMachine LearningJiraQuality AssuranceComputer Vision

BS degree in Computer Science, Engineering, Electrical Engineering, or equivalent experience.
2–5 years of experience in ML QA, annotation quality, data quality, or analytics in an AI/ML environment.
Hands-on experience with annotated ML or computer vision datasets, including label quality assessment.
Strong statistical and analytical capabilities with the ability to identify patterns from noise.
Proven root cause analysis skills, including the ability to develop and test competing hypotheses.
Proficiency in Python and SQL to investigate datasets independently.
Experience creating quality guidelines, decision rules, labeling taxonomies, or SOPs.
Strong written communication skills for producing clear technical reports.
Experience with enterprise ticketing systems like Jira.
Understanding of data privacy and confidentiality requirements.

Own quality analysis of annotated ML and computer vision data, managing daily review queues and root-cause assessments.
Define and refine verdict taxonomies, decision rules, quality guidelines, and annotation standards.
Build and maintain performance trackers to measure error rates across facilities, equipment, and data formats.
Conduct root cause analysis to distinguish between annotation errors, model failures, and system issues.
Communicate findings and documented failure patterns to ML, QA, and engineering stakeholders.
Use Python and SQL to independently query and analyze annotation data.
Translate quality findings into improvements for annotation SOPs and tool functionality.
Track work through Jira and contribute to pre-release validation for relevant workflows.

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