Product QA Engineer - SAR & EO Image Validation
GALAXEYE SPACE SOLUTIONS PRIVATE LIMITED Yelahanka taluku, Karnataka, India
Defense and Space Manufacturing · 51-200 employees
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About the role
The QA Engineer will perform structured testing and validation of SAR and EO imagery products, AI/ML model outputs, and associated analysis applications. They are responsible for end-to-end product QA, including test planning, defect management, and maintaining audit-ready QA processes.
What they look for
Requirements
Candidates must hold a bachelor's or master's degree in a relevant field such as Remote Sensing, GIS, Physics, or Computer Science. The role requires 2–3 years of experience in QA testing, familiarity with SAR/EO imagery, and basic Python scripting skills.
Benefits
Full description
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.
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