QA Engineer

Role Overview
As our QA Engineer, you will be responsible for developing and executing test plans that validate the functionality and performance of our AI-driven applications. You will work closely with data scientists, software engineers, and product managers to ensure our solutions are rigorously tested and meet the highest standards before deployment.

Key Responsibilities
Design & Implement Test Plans


Develop comprehensive testing strategies (including functional, integration, system, regression, and performance testing) for AI-centric applications.
Ensure thorough coverage of edge cases, corner cases, and high-risk areas.
Automation & Continuous Integration


Build and maintain automated test frameworks for backend, frontend, and AI model validation.
Integrate test automation into continuous integration (CI) pipelines to detect issues early and improve delivery speed.
AI Model Validation & Performance Testing


Validate the accuracy and performance of machine learning models, ensuring they meet established KPIs.
Design tests to evaluate model robustness, bias, and failure modes.
Collaborate with data scientists to reproduce and debug issues related to data pipelines or model outputs.
Defect Tracking & Reporting


Investigate, document, and communicate defects, including detailed steps to reproduce and potential root causes.
Track bug resolution and verify fixes, providing clear updates to cross-functional teams.
Collaboration & Process Improvement


Work closely with developers and product managers, contributing to product requirements and acceptance criteria from a QA perspective.
Champion best practices and continuous improvement in QA processes and methodologies for AI-based systems.
Compliance & Security Testing


Ensure adherence to relevant data privacy and compliance standards.
Implement security testing measures to protect AI models and data pipelines from potential threats.

Qualifications
QA Expertise: Proven experience in QA and software testing, with strong knowledge of test methodologies, tools, and processes (e.g., Selenium, Cypress, PyTest).
AI/ML Knowledge: Familiarity with machine learning concepts, AI pipelines, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Automation Skills: Hands-on experience creating and maintaining automated tests in a CI/CD environment (e.g., Jenkins, GitLab CI, GitHub Actions).
Programming Languages: Proficiency in Python or a similar language; ability to review, debug, and provide feedback on code.
Analytical Mindset: Strong problem-solving skills and the ability to troubleshoot complex issues effectively.
Communication: Excellent written and verbal communication skills, with the ability to collaborate effectively across teams.

Preferred Qualifications
Experience testing cloud-based AI solutions (AWS, Azure, or GCP).
Knowledge of containerization and orchestration (Docker, Kubernetes).
Familiarity with model interpretability tools and AI/ML best practices (e.g., bias detection, fairness testing).
ISTQB or other relevant QA certifications.

How to Apply
If you are interested, please send your resume, portfolio/github, and a quick video going over your experience. Send these materials to ----------