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SDET 2

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Description

We are looking for an experienced SDET 2 / Software Development Engineer in Test with strong hands-on experience in Python, test automation, and PyTorch. The candidate will be responsible for building and maintaining automated test frameworks, validating AI/ML applications and models, and ensuring the quality, reliability, and performance of software products.


Responsibilities:

  • Design, develop, and maintain automated test frameworks using Python.
  • Develop automated test cases for functional, regression, integration, and end-to-end testing.
  • Work with PyTorch-based AI/ML models and applications to validate model behaviour, outputs, and integration.
  • Build testing strategies for AI/ML pipelines, APIs, and data workflows.
  • Perform API testing and automation for REST/HTTP-based services.
  • Identify, troubleshoot, and debug issues across application and ML/model layers.
  • Create reusable automation utilities and improve test coverage.
  • Integrate automated test suites with CI/CD pipelines.
  • Work closely with developers, ML engineers, and product teams to identify quality risks.
  • Perform test execution, defect tracking, root-cause analysis, and reporting.
  • Contribute to improving automation frameworks, test processes, and overall product quality.


Requirements:

  • 4-7 years of experience in SDET / QA Automation / Software Testing.
  • Strong programming experience in Python.
  • Hands-on experience with PyTorch.
  • Strong experience in test automation and framework development.
  • Experience with PyTest / unittest.
  • Good understanding of API testing and automation.
  • Experience with Git and CI/CD tools.
  • Strong debugging and problem-solving skills.
  • Good understanding of SDLC, STLC, and software testing methodologies.


AI/ML Testing Skills:

  • Understanding of Machine Learning / Deep Learning concepts.
  • Experience testing PyTorch models or ML-based applications.
  • Understanding of model inputs, outputs, inference and validation.
  • Experience validating data pipelines or ML workflows is an advantage.
  • Knowledge of model performance, accuracy, and edge-case testing is preferred.


Good to Have:

  • Selenium / Playwright
  • REST Assured or Python API automation
  • Docker
  • Kubernetes
  • Jenkins / GitHub Actions / GitLab CI
  • AWS / Azure / GCP
  • SQL
  • TensorFlow
  • MLflow
  • Kafka
  • Performance testing

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