A QA Engineer's Journey into AI/ML Testing
This is the first article by a senior software testing engineer who is learning about building, deploying, and testing machine learning and AI systems. They aim to share practical insights from a QA perspective.
Why it matters
This article series can provide valuable insights for QA engineers, software developers, and ML practitioners on testing and validating AI/ML systems.
Key Points
- 1The author is a senior software testing engineer with 9 years of experience
- 2They have recently started learning about machine learning and AI systems
- 3This article series will document their learning journey and share insights for QA, software engineers, and ML practitioners
- 4The author is looking for feedback, questions, and different perspectives from the community
Details
The author of this article is a Senior Software Development Engineer in Test (SDET) with 9 years of experience in software testing and quality engineering. They have recently started learning about how machine learning and AI systems are built, deployed, and tested. Through this new article series, they aim to document their learning journey and share practical insights from a QA and testing perspective that can be applied by engineers working on real-world AI/ML systems. The author is hoping to reach out to QA engineers, software developers, data/ML practitioners, and anyone else who is curious about testing AI systems. By sharing their experiences and learning, they hope to foster a collaborative environment where the community can provide feedback, ask questions, and offer different perspectives.
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