Manager, AI Data Ops

ProducePay; Bengaluru; On-site; INR 450,000 - 750,000; Full time

Job summary

AiDASH is seeking an accomplished Manager – AI Data Ops to lead a team responsible for sourcing, processing, and annotating satellite imagery that powers our AI/ML models. You will blend hands-on GIS expertise with strong people management and vendor coordination to ensure high-quality data pipelines.

Ideal candidates have deep experience with satellite imagery, remote sensing data sourcing, and managing both in-house and external annotation partners, driving automation and scalable processes.

Qualifications

• 8+ years of experience in GIS, remote sensing, or geospatial data operations.
• Minimum 2+ years of direct people management experience.
• Proven experience handling third-party vendors/BPOs and SLA management.
• Strong understanding of QA/QC frameworks for spatial data and annotation accuracy.
• Experience driving automation in annotation/data labeling workflows.

Responsibilities

• Lead end-to-end sourcing of satellite imagery and remote sensing datasets from multiple providers.
• Oversee image annotation and labeling workflows for land cover, vegetation, asset monitoring, and change detection.
• Define and improve annotation guidelines, taxonomies, and labeling protocols with Data Science and ML teams.
• Manage a team of GIS analysts/annotators, implement capacity planning and skill development.
• Coordinate with cross-functional teams to align annotation outputs with project timelines.

Skills

GIS

Remote Sensing

Team Leadership

Vendor Management

Data Pipelines

Education

Geography / GIS degree

Tools

ArcGIS

QGIS

Google Earth Engine

ERDAS Imagine

ENVI

CVAT

Labelbox

SuperAnnotate

Job description

About AiDASH

AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com.

The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024.

Join us in Securing Tomorrow Together!

The Role

AiDASH is looking for an experienced Manager – AI Data Ops to lead a team responsible for sourcing, processing, and annotating satellite and remote sensing imagery that powers our AI/ML models. This role blends hands‑on GIS expertise with strong people management and vendor coordination skills, and is central to ensuring high‑quality, timely, and scalable geospatial data pipelines.

The ideal candidate has deep experience working with satellite and aerial imagery, understands the nuances of remote sensing data sourcing, and has successfully managed both in‑house annotation teams and external vendor partners.

How you'll make an impact:

GIS & Remote Sensing Operations

• Lead end-to-end sourcing of satellite imagery, aerial data, and remote sensing datasets from various providers (e.g., optical, SAR, multispectral, hyperspectral sources).

• Oversee image annotation and labeling workflows for use cases such as land cover classification, vegetation/asset monitoring, infrastructure mapping, and change detection.

• Ensure annotation accuracy, consistency, and adherence to defined quality standards (QA/QC frameworks) across all delivered datasets.

• Define and continuously improve annotation guidelines, taxonomies, and labeling protocols in collaboration with Data Science and ML teams.

• Stay current with GIS tools, remote sensing platforms, and annotation technologies (e.g., QGIS, ArcGIS, ERDAS, Google Earth Engine, CVAT, Labelbox, or similar).

People Management

• Manage, mentor, and grow a team of GIS analysts/annotators (team size: specify, e.g., 15–40+), including performance reviews, capacity planning, and skill development.

• Build a strong bench of GIS talent through structured hiring, onboarding, and training programs.

• Drive productivity, quality, and throughput targets across the team through KPIs and process discipline.

• Foster a collaborative, high-accountability team culture.

Vendor & Stakeholder Management

• Identify, evaluate, and onboard third-party vendors/BPOs for image annotation and data labeling at scale.

• Negotiate SLAs, pricing, and turnaround commitments with vendor partners; monitor ongoing performance against these agreements.

• Act as the primary point of contact for vendor escalations, quality issues, and capacity scaling needs.

• Coordinate cross-functionally with Data Science, Engineering, Product, and Delivery teams to align annotation output with project timelines and model requirements.

Process & Reporting

• Build dashboards/reports to track annotation throughput, accuracy metrics, vendor performance, and cost efficiency.

• Identify opportunities for automation/semi-automation in the annotation pipeline (e.g., active learning loops, pre-labeling with models) to improve efficiency.

• Manage budgets related to data sourcing, annotation operations, and vendor contracts.

Who we're looking for:

• 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) and 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.

We are proud to be an equal-opportunity employer.

We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.

We are committed to providing an inclusive and accessible interview experience for all candidates.

Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs.

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