Product QA Engineer - SAR & EO Image Validation

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.