AI Data Quality Lead – Robotics & Video Annotation | Remote

About the Role

We are looking for an experienced AI Data Quality Lead to own the quality standards for egocentric training data used to develop and evaluate physical-AI and robotics models.

You will be responsible for building and maintaining the golden sets, annotation SOPs, rubrics, calibration systems, quality frameworks, and audit processes that ensure high-quality ground-truth data. You will also work closely with engineering and product teams to develop annotation workflows for hand tracking, object identification, and action labeling.

This is a ground-floor prospect to build a 0→1 data quality system at a fast-growing, well-funded startup. You will not simply inherit an existing process—you will help establish the quality standards, workflows, and systems from the ground up.

Key Responsibilities

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Own the end-to-end quality framework for egocentric training data, including:

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Golden and benchmark datasets

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Acceptance criteria

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Frame-level tolerance thresholds

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Sampling strategies

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Audit and quality-control loops

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Author, maintain, and version annotation SOPs, rubrics, and edge-case guidelines as project specifications evolve.

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Translate ambiguous requirements into precise, actionable instructions for annotators and reviewers.

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Establish and manage annotator training, certification, and calibration programs.

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Run calibration sessions and adjudicate disagreements between annotators.

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Measure and report quality using metrics such as:

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Inter-Annotator Agreement (IAA)

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Kappa/alpha

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Tolerance-based agreement for temporal boundaries

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Acceptance/rejection rates

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Rework rates

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Cost per accepted hour

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Identify root causes of quality issues and determine whether they result from guideline ambiguity, annotation errors, or workflow issues.

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Design human-in-the-loop workflows where AI/model-generated labels are reviewed, corrected, and escalated by human annotators.

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📌 Data Annotation Lead (India)
🏢 Yo HR Consultancy
📍 India