Software Development Engineer in Test - SDET Dallas, TX, 75001, Dallas-TX

Software Development Engineer in Test - SDET

Part Time • Dallas, TX, 75001, Dallas-TX
SDET 
Dallas, TX
 
 
Responsibilities
  • Design, develop, and maintain test automation frameworks using Python and/or Java.
  • Build automated test suites for functional, regression, performance, and integration testing.
  • Participate in testing of AI/ML models, including validating outputs, datasets, model accuracy, and edge-case behaviors.
  • Implement AI-assisted testing tools and contribute to developing intelligent test solutions.
  • Collaborate with cross-functional teams to understand product requirements and convert them into test strategies.
  • Identify root causes of defects and work with engineering teams to resolve them.
  • Perform code reviews, maintain test documentation, and ensure best testing practices.
  • Contribute to CI/CD pipelines with automated quality gates.
  • Continuously evaluate and integrate new tools, frameworks, and AI capabilities to improve test efficiency.

Required Skills & Qualifications
  • Bachelor’s degree in computer science, Engineering, or related field (or equivalent experience).
  • Strong experience in test automation using Python and/or Java.
  • Solid understanding of testing methodologies, QA processes, and automation principles.
  • Exposure to AI/ML concepts such as model training, model inference, datasets, bias, and evaluation metrics.
  • Experience working with API testing tools (e.g., Postman, REST Assured, PyTest).
  • Hands-on experience with automation frameworks like Selenium, Playwright, Cypress, or Robot Framework.
  • Familiarity with CI/CD platforms (Jenkins, GitHub Actions, GitLab CI, etc.).
  • Strong analytical and debugging skills.

Preferred Qualifications
  • Experience testing AI/ML pipelines or platforms.
  • Understanding of LLMs, NLP, generative AI, or ML workflows.
  • Knowledge of cloud platforms (AWS, Azure, GCP).
  • Experience with containerization tools (Docker, Kubernetes).
  • Familiarity with data validation, data quality tools, or synthetic data generation.
  • Experience with test-case generation using AI tools.
 




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