Job Description
Job DescriptionAbout the role:
We’re seeking computer science interns to build a production-style QA platform delivered as a Streamlit app. The app will trigger and monitor DRC runs, track cycle time (days to completion), iteration history, and rule stability, and provide a simple in-app chatbot for common engineer FAQs.
What you will do:
- Build a multipage Streamlit app (navigation, session state, role-based views).
- Pages for creating/launching QA runs, monitoring progress, and reviewing results.
- KPI dashboards for cycle time (days), pass/fail rates, iteration counts, and stability trends.
- Robust error handling, caching, and handling of long-running/background tasks.
[DRC integration and results processing]
- Integrate with a DRC tool (e.g., KLayout or Calibre if available) to execute checks from the app.
- Parse and normalize DRC reports; link violations to rule IDs, run IDs, and timestamps.
[Rule registry and stability tracking]<...
We’re seeking computer science interns to build a production-style QA platform delivered as a Streamlit app. The app will trigger and monitor DRC runs, track cycle time (days to completion), iteration history, and rule stability, and provide a simple in-app chatbot for common engineer FAQs.
What you will do:
- Build a multipage Streamlit app (navigation, session state, role-based views).
- Pages for creating/launching QA runs, monitoring progress, and reviewing results.
- KPI dashboards for cycle time (days), pass/fail rates, iteration counts, and stability trends.
- Robust error handling, caching, and handling of long-running/background tasks.
[DRC integration and results processing]
- Integrate with a DRC tool (e.g., KLayout or Calibre if available) to execute checks from the app.
- Parse and normalize DRC reports; link violations to rule IDs, run IDs, and timestamps.
[Rule registry and stability tracking]<...
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