Engineering

Surgical Video Data & Annotation Operations Manager (Pune)

Pune, Maharashtra
Work Type: Full Time
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

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.

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