Netflix
Senior
Own the internal Python 'Paved Path' platform used across Netflix's ML, Data Science, and Animation domains
This role builds Netflix's internal application development platform for Python, evolving it from a supported language into a fully managed, opinionated 'Paved Path' used across Machine Learning, Data Science, and Animation. It demands deep internal Python mechanics knowledge (execution model, dependency resolution, packaging), authoring libraries used across batch/streaming/web contexts, and expertise in frameworks like FastAPI/Flask — plus running large-scale automated refactors across thousands of repos. This is a senior platform-engineering IC role, not application feature work.
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What this interview tests
- Deep Python internals: execution model, dependency resolution, packaging
- Authoring cross-environment libraries (batch, streaming, training, web)
- Python web framework expertise (FastAPI, Flask)
- Large-scale, safe automated refactors across many repositories
- Developer-experience-driven platform design ('paved path')
- Judicious application of GenAI tools to platform workflows
Common question themes
Explain the Python execution model and a dependency-resolution problem you've solved at scale
Describe a Python library you built that had to run across batch, streaming, and web contexts
Walk me through an architectural decision you made using FastAPI or Flask
How have you executed a massive, safe code refactor across thousands of repositories?
Tell me about designing a developer platform by working backward from engineers' actual needs
How do you balance adopting new best practices against conservative, risk-aware platform changes?
How have you applied GenAI tools with judgment to improve an engineering workflow?
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