Title: Surgical Video Data & Annotation Operations Manager

Location: Pune

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Role Summary

Own and scale a production pipeline that ingests, de-identifies, annotates, and delivers 10,000+ hours/month of surgical video with ≥70% automation and audit-ready compliance. You will design the ontology, stand up model-in-the-loop labeling, run QA/IAA, and hit SLAs from ingest → labeled → approved datasets for training and evaluation.

Core Responsibilities

1) Program Ownership & Throughput

- Deliver ≥10,000 labeled video hours/month within SLA (≤7 days ingest→approved).
- Maintain ≥70% auto-accept rate via model-assisted labeling; drive to 80%+ over time.
- Operate daily pipeline: ingest → de-id → pre-labels → annotation → QA → release.
- Manage backlog, staffing,



and shift planning to sustain 333+ hours/day throughput.

2) Ontology & Guidelines

- Define and version surgical ontologies: phases, steps, events, tools, anatomy, quality flags.
- Author annotation guidelines with boundary rules and ambiguity handling.
- Run change control and backward compatibility across dataset versions.

3) Tooling & Automation

- Stand up and operate CVAT (or equivalent) with API-driven workflows.
- Integrate MONAI Label (or similar) for model-assisted segmentation/active learning.
- Use FiftyOne (or equivalent) for dataset QA, error analysis, and sampling.
- Implement propagation (tracking/interpolation) and confidence-based routing.
- Partner with ML to deploy pre-label models (tool detection, phase recognition, SAM-style masks).

4) Quality, IAA & Release Gates

- Define gold sets and acceptance thresholds:
- Phase/event F1 ≥ 0.92
- Tool mAP ≥ 0.85
- Anatomy Dice ≥ 0.85
- Run double-labeling (≥10%), adjudication, and weekly QA reviews.

📌 Surgical Video Data & Annotation Operations Manager (Pune)
🏢 Codvo.ai
📍 Pune