GalaxEye

Product QA Engineer - SAR & EO Image Validation

Bengaluru, Karnataka · Full time · 1-3 years

Posted
2 Sept 2026
Last verified at source
6 hours ago
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About GalaxEye

GalaxEye is a Space-Tech startup pioneering the world's first OptoSAR, integrating SAR (Synthetic Aperture Radar) and MSI (Multi-Spectral Imaging) on a single platform. As we move towards building a constellation of indigenous satellites, we are also developing advanced data platforms that fuse satellite data, AI analytics, and geospatial intelligence.

About the role

We are seeking a QA/QC Engineer responsible for the structured testing and validation of SAR and EO imagery products, AI/ML model outputs, and the associated image analysis applications.

This is a testing-first role with end-to-end ownership of product QA, responsible for:

  • Validation of SAR/EO imagery and AI/ML model outputs
  • End-to-end application and workflow testing
  • Smoke, functional, exploratory and regression testing across releases
  • Structured defect tracking and verification
  • QA automation, reporting and release validation
  • Maintaining repeatable, audit-ready QA processes

The role is expected to operate independently from development and processing teams, providing an objective assessment of product quality and release readiness.

Key Responsibilities

A. Image & Model Output Validation

●        Inspect SAR and EO imagery for distortions, inconsistencies and other quality issues.

●        Validate model outputs including detections, classifications, annotations and overlays against defined benchmarks.

●        Identify false positives, missed detections, localization errors and recurring model failure patterns.

●        Perform regression validation when models, processing pipelines or module configurations are changed.

●        Provide structured QA inputs and independent assessment of release readiness prior to internal release or customer delivery.

B. End-to-End Product & Release Testing

●        Test complete image analysis workflows from data ingestion through processing, analysis and visualization.

●        Validate application functionality, UI workflows, overlays, annotations, layers and analysis outputs.

●        Perform functional, smoke, exploratory and regression testing across standalone and server-based product versions.

●        Maintain reusable smoke and regression test suites to support frequent product releases.

●        Verify fixes and ensure changes do not introduce regressions elsewhere in the system.

C. Test Planning and Automation

●        Develop and continuously improve structured test cases, regression suites, checklists and QA workflows covering imagery, model outputs and application functionality.

●        Identify gaps in test coverage, tooling and processes and implement improvements to increase QA efficiency and coverage.

●        Identify repetitive QA activities suitable for automation and build Python-based scripts and utilities where feasible.

●        Maintain reusable test templates and frameworks to support rapid release cycles.

D. Defect and Issue Management

●        Identify, document and classify defects with clear reproduction steps, evidence, severity and priority.

●        Track defects through resolution, retesting and closure.

●        Maintain structured visibility of issues by product version, module, defect type, status and customer/deployment location.

●        Track recurring, unresolved and deferred issues across releases and highlight systemic quality concerns.

E. QA Reporting & Documentation

●        Maintain structured reports for feature, smoke, regression and release testing.

●        Maintain test cases, execution records, checklists, defect logs and supporting evidence.

●        Establish reusable reporting templates to support rapid release cycles and consistent QA practices.

●        Generate summaries of open issues, recurring defects, regression status and release readiness.

●        Ensure QA results are reproducible, traceable and audit-ready, including support for customer-facing quality documentation.



Requirements

Required Qualifications:

●        Bachelor’s/Master’s degree in Remote Sensing, Geoinformatics, GIS, Physics, Electrical Engineering, Computer Science or a related field.

●        2–3 years of experience in QA/testing roles, preferably involving image, data-heavy or software products.

●        Experience with manual, functional, regression and end-to-end testing.

●        Experience or familiarity with SAR and/or Electro-Optical imagery analysis.

●        Familiarity with image analysis/GIS tools such as QGIS, SNAP, ENVI or equivalent.

●        Basic Python scripting skills for test automation and data validation.

●        Strong documentation, reporting and defect-tracking skills.

●        Strong analytical thinking, attention to detail and systematic problem-solving ability.


Preferred:

●        Experience testing AI/ML-based image analysis or computer vision outputs.

●        Exposure to model accuracy validation, benchmarking or dataset QA.

●        Experience building automated QA or regression testing utilities.

●        Familiarity with version-controlled release testing.

●        Experience testing standalone and server-based applications.

●        Experience supporting customer deployments, UAT, acceptance testing or audit processes.

●        Experience in startup or fast-iteration product environments.

●        Familiarity with geospatial, satellite imagery, remote sensing or defence applications.



Benefits

  • Hands-on experience working with SAR, EOl imagery and AI-driven image analysis.
  • Opportunity to own and build QA processes, test frameworks and automation for a growing product.
  • Exposure to end-to-end product testing, rapid release cycles, customer deployments and audit-ready QA.
  • Work at the intersection of software, geospatial technology, computer vision and space-tech.
  • High ownership and the opportunity to influence product quality directly and release readiness.