Product QA Engineer - SAR & EO Image Validation

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.

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.

• 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.