Quality Assurance Engineer

【About the Role】
As a Quality Assurance Engineer, you will establish the testing processes and quality guardrails that help ensure every software release meets our standards for correctness, reliability, performance, and usability.
You will work across our frontend/backend applications, machine learning pipelines, GPU workloads, and production systems to develop scalable and repeatable testing strategies. A major focus of this role is turning testing requirements into automated workflows that can detect regressions early and provide teams with confidence when releasing new versions.
You will work closely with engineering teams and product stakeholders to define quality standards, improve test coverage, and ensure that releases are ready for production use.

【Responsibilities】

• Define and maintain QA policies, release criteria, and automated testing procedures covering frontend interfaces, backend APIs, machine learning components, GPU workloads, and integrated product workflows.
• Develop reusable and scalable regression-testing systems, test environments, datasets, and validation workflows that identify changes in correctness, runtime performance, memory usage, system configuration, and overall product behavior across releases.
• Collaborate with engineering and DevOps teams to understand existing unit, integration, and system tests, expand the required coverage, and integrate automated quality gates into CI/CD and release pipelines.
• Investigate failed tests, reproduce reported issues, identify potential causes of regression, and communicate clear findings and risks to the relevant engineering teams.
• Document test plans, validation results, known limitations, release risks, and quality decisions in a clear and traceable manner.

【Key Qualifications】

• Strong programming and software engineering fundamentals, with proficiency in Python or other relevant languages used for test automation.
• Experience designing automated integration, system, end-to-end, and regression tests, with an understanding of QA methodologies, release criteria, risk-based testing, and testing complex software such as APIs, user interfaces, and backend services.
• Ability to design repeatable and scalable testing frameworks and workflows rather than relying primarily on manual validation.
• Experience working with production software that requires controlled releases, high reliability, and strong regression protection.
• Familiarity with Git-based development workflows and CI/CD practices.
• Strong analytical, problem-solving, communication, and collaboration skills, with the ability to investigate failures and explain quality risks clearly.

【Preferred, but Not Required】

• Experience with automated frontend, GUI, API, and service-level integration testing.
• Experience building reusable test frameworks, test environments, test-data management processes, simulation tools, or hardware-in-the-loop testing workflows.
• Familiarity with containerized test environments and automated quality gates using technologies such as Docker and CI/CD platforms.
• Experience validating runtime performance, resource utilization, system settings, and hardware-dependent behavior in performance-sensitive or data-intensive applications.
• Familiarity with machine learning systems and the ability to evaluate regressions involving model outputs, evaluation metrics, inference behavior, or training workflows.
• Experience testing GPU-accelerated machine learning applications or other hardware-dependent workloads.

You do not need to match every preferred qualification. We value systematic thinking, strong automation skills, attention to detail, and the ability to build testing processes that help engineering teams release software with confidence. We are hiring for both mid-level and senior-level engineering positions, and the scope and expectations of the role will be considered based on your experience and seniority during the interview process.