Align Technology
Posted Today
SQA Engineer, Machine Learning
APAC-India-IT Delivery Center HyderabadOn-siteFull-time
AI Summary
About the RoleAs a Machine Learning SQA Engineer, you will design and execute test automation and validation systems that ensure the reliability, accuracy, and consistency of AI and ML-based applications.
About this role
About the Role
As a Machine Learning SQA Engineer, you will design and execute test automation and validation systems that ensure the reliability, accuracy, and consistency of AI and ML-based applications. You’ll help bridge classic software QA principles with emerging AI quality challenges — validating large language model (LLM) outputs, data pipelines, and AI-driven APIs.
As a Machine Learning SQA Engineer, you will design and execute test automation and validation systems that ensure the reliability, accuracy, and consistency of AI and ML-based applications. You’ll help bridge classic software QA principles with emerging AI quality challenges — validating large language model (LLM) outputs, data pipelines, and AI-driven APIs.
This role is ideal for a QA engineer with strong automation skills and growing experience in AI or data-centric systems, who is eager to apply proven testing discipline to next-generation intelligent products.
Key Responsibilities
Key Responsibilities
- Develop, maintain, and execute automated and manual test cases for AI/ML systems, APIs, and data pipelines.
- Build and enhance test automation frameworks to validate LLM or ML model outputs and integrations.
- Test AI agent workflows and monitor system performance, reliability, and output consistency.
- Collaborate with engineers and data scientists to diagnose, document, and track defects.
- Evaluate LLM and prompt behavior against predefined benchmarks and edge cases.
- Participate in code reviews and provide feedback on testability and quality standards.
- Contribute to continuous integration and delivery (CI/CD) testing processes and pipelines.
- Maintain test documentation, datasets, and metrics to track system health and quality trends.
- Research and propose new QA methodologies for AI and ML systems (“AI testing AI”).
Skills, Knowledge & Expertise
Required Skills & Experience
- 5-8 years of experience as an SQA, Test Automation, or QA Engineer (preferably with exposure to data or ML systems).
- Proficiency in Python and one or more of: JavaScript, Java, or TypeScript for automation scripting.
- Strong understanding of software testing principles, test case design, and defect lifecycle management.
- Experience building or maintaining test automation frameworks (e.g., PyTest, Cypress, Selenium, Playwright).
- Working knowledge of SQL and structured data validation.
- Familiarity with ML/LLM fundamentals and evaluating model outputs.
- Experience testing RESTful APIs and using tools such as Postman or pytest-requests.
- Exposure to cloud environments (AWS, GCP, or Azure) and CI/CD pipelines (e.g., GitHub Actions, Jenkins).
Preferred Attributes
- Curiosity to learn emerging AI technologies and apply traditional QA methods to new paradigms.
- Analytical mindset with strong systems thinking — able to understand and test full workflows.
- Ability to visualize and communicate complex test scenarios.
- Comfort working in dynamic, iterative environments where experimentation drives improvement.