QA Engineer/Analyst Job

a. Develop and implement comprehensive QA strategies tailored for AI/ML-based applications, ensuring quality across the entire machine learning lifecycle.
b. Define and execute functional, integration, regression, performance, and security testing methodologies to validate end-to-end system stability.
c. Design detailed test cases focusing on AI model behavior, accuracy, prediction reliability, and edge-case handling for ML-driven products.
d. Execute test scenarios, document testing outcomes, and communicate insights effectively to technical and non-technical stakeholders.
e. Validate AI model outputs by assessing accuracy, consistency, and fairness across diverse datasets and real-world conditions.
f. Conduct benchmarking to monitor model drift, performance variations, and degradation over time.
g. Review, verify, and assess datasets used for training and testing models, ensuring data completeness, quality, and relevance.
h. Identify anomalies, biases, and data gaps that may affect model predictions, and escalate issues proactively.
i. Develop and implement automated test frameworks to support AI/ML systems, integrating with CI/CD pipelines for continuous validation.
j. Leverage tools such as Selenium, PyTest, and JUnit to standardize automated test execution and improve test reliability.
k. Log and track defects with complete traceability, facilitating timely resolution through collaboration with AI developers and data scientists.
l. Analyze QA results to recommend improvements to AI models, datasets, and overall development processes.
m. Continuously optimize testing strategies to align with evolving AI/ML technologies, tools, and best practices.
n. Maintain detailed documentation of QA plans, test cases, test results, and model validation reports to ensure transparency and reproducibility.
o. Prepare clear, concise, and actionable reports that support data-driven decision-making for product and engineering teams.
p. Collaborate closely with AI engineers, data scientists, product owners, and cross-functional teams throughout the model development and deployment lifecycle.
q. Provide QA insights during design, development, testing, and post-deployment stages to ensure product readiness and reliability.
r. Ensure compliance with industry standards, regulatory requirements, and AI ethics principles, including fairness, transparency, and accountability.
s. Validate model outputs against ethical guidelines to minimize bias and ensure responsible AI deployment.
t. Utilize cloud platforms such as Azure and containerization tools like Docker and Kubernetes to support scalable testing environments.
u. Apply programming skills in Python, R, and SQL to support automation, data validation, and model verification tasks.

Bachelors degree and 5 years of experience are required

Please mail resumes to:

Broadaxis, Inc.
Human Resources
101 E Park Blvd
Suite 905
Plano, TX 75074