Quality Assurance Manager

Job Description

Locations: Rochester, New York

Categories: Operations

Job Type: Regular Full‑Time

Work Type: Remote

Eagleview® is a leading provider of aerial imagery, property insights and software that transforms the way people work. Eagleview holds more than 300 patents and owns a large geospatial data and imagery library encompassing 94 percent of the US population. Eagleview provides the most accurate data, enabling customers in the government, construction, solar and insurance industries to make timely, informed and better decisions.

Eagle View, the leader in aerial imagery, is hiring a Quality Assurance Manager for Digital Content. The Quality Assurance Manager Digital Content is responsible for the end-to-end quality, validity, governance, and auditability of Eagle View's 2D building footprints and feature outlines. This role ensures that geospatial data products—regardless of source, including machine‑learning outputs, third‑party vendors, partner feeds, and authoritative mapping datasets—meet enterprise‑grade standards for geometric integrity, positional accuracy, completeness, and statistical defensibility.

The primary focus is establishing scalable geospatial data quality frameworks across diverse data inputs, with machine‑learning serving as one of several contributing sources rather than the central emphasis.

We are a fast‑paced, energetic team driven by continuous process improvement. We're looking for motivated, organized, and independent team members. This role requires good communication skills and the ability to quickly pick up new technologies.

This is a full‑time, remote role with a base salary of $72,100–$89,500 with a 10% bonus potential.

• Work with Product, Sales, and Customer Success to define product quality expectations.
• Works closely with the Operations Quality Manager for Imagery Content to ensure that quality assurance is maintained throughout all operational processes.
• Works with technology and engineering teams to design quality processes, the tooling to implement processes, and continuous improvement of workflows.
• Establish metrics and tools to measure product quality and production capability levels and ensure that quality outputs meet or exceed product expectations, including inputs from third parties and other external sources.
• Improve reliability and performance of workflows through the utilization of lean methodology and optimization of computer vision/machine‑learning technology.
• Investigate, measure, and recommend remediation of root cause system failures related to production defects, including processing tools and software.
• Support the design, implementation, and auditing of formal quality control and assurance procedures, including checks and balances throughout the process.
• Develop acceptance testing protocols and implement sufficient feedback loops to inform operational considerations on image quality, product usability trends, and issues.
• Review released engineering change data and changes documenting activities to ensure adherence to configuration management procedures and policies.
• Other duties as assigned

• Bachelor's degree in geospatial sciences, applied mathematics, engineering, land surveying, or related disciplines
• 3‑5 years of direct experience in data quality, ML operations, geospatial quality assurance, or computer vision systems.
• Experience working with Lean or Agile management systems, ISO, Six sigma, continuous improvement, quality, or configuration management (CMMI) methods and tools.
• Strong root cause analysis skills and ability to provide useful feedback on product design and failure modes related to optical equipment.
• Strong understanding of polygon geometry and topology, raster‑to‑vector workflows, Machine Learning confidence, and uncertainty concepts.
• Experience designing automated quality gates in production workflows.
• Comfortable working with large‑scale, automated systems where manual review is the exception, not the norm.
• Ability to reason about edge cases, failure modes, and tradeoffs at scale.
• Experience with aerial or satellite imagery.
• Familiarity with object detection/segmentation workflows.
• Background…