Job Description
About 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]
- Implement a rule registry with metadata (ID, description, deck reference, owners, severity, status).
- Track rule updates, QA history, and compute stability signals (no-change windows, regression flags).
[Data model and storage]
- Design schemas for runs, results, rules, and artifacts (PostgreSQL or SQLite).
- Persist logs, reports, and attachments with traceable metadata and audit trails.
[In-app basic chatbot]
- Add a simple chatbot to answer FAQs (how to run QA, rule descriptions, common errors) using lightweight retrieval over internal docs.
Requirement
- Bachelor's Degree/ Master's Degree/ PhD in Computer Science / Computer Engineering / Electrical and Electronics Engineering.