Manager, AI Data Ops
On-siteBengaluru, Karnataka, India
Job Summary
Lead end-to-end sourcing of satellite and aerial imagery from multiple providers, then oversee annotation workflows for land cover classification, vegetation monitoring, and infrastructure mapping. Define annotation guidelines, taxonomies, and labeling protocols in collaboration with Data Science teams while ensuring QA/QC adherence across all datasets. Manage a team of GIS analysts and mentors, drive productivity through KPIs, and coordinate cross-functionally with Product and Engineering to align output with model requirements. Identify and onboard third-party vendors, negotiate SLAs, and monitor performance against capacity and quality targets. Build dashboards to track throughput and accuracy, and identify automation opportunities to improve pipeline efficiency.
Required Qualifications
- 8+ years of overall experience in GIS, remote sensing, or geospatial data operations
- minimum 2+ years managing teams directly
- Strong hands-on knowledge of satellite imagery sourcing (optical, SAR, multispectral) and remote sensing data pipelines
- Proven experience managing image annotation/data labeling teams and processes at scale
- Demonstrated experience handling third-party vendors/BPOs — including contracting, SLA management, and performance monitoring
- Proficiency with GIS software (ArcGIS, QGIS)
- familiarity with remote sensing platforms (Google Earth Engine, ERDAS Imagine, ENVI, etc.)
- Working knowledge of annotation/labeling tools (CVAT, Labelbox, SuperAnnotate, or in-house tools)
- Track record of driving automation heavily in previous roles — replacing manual/repetitive steps with tools, scripts, or AI-assisted workflows
- An "AI-native" way of working — comfortable using LLMs/AI copilots as part of daily workflow (analysis, documentation, communication, process design), not just as a novelty
- Experience working with AI/ML teams and understanding of how annotated data feeds into model training
- Strong understanding of quality frameworks (QA/QC) for spatial data and annotation accuracy
- Excellent communication, stakeholder management, and cross-functional collaboration skills
- Bachelor's/Master's degree in Geography, GIS, Remote Sensing, Geoinformatics, Environmental Science, or a related field
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