Title: Surgical Video Data & Annotation Operations Manager
Location: Pune
About Us
At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.
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
- Program Ownership & Throughput
- Deliver 10,000 labeled video hours/month within SLA (7 days ingestapproved).
- 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.
- 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.
- 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).
- 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.
