Debug ML pipeline and build text parser

Q: Debug ML pipeline and build text parser

This question evaluates skills in robust text parsing, data cleaning, debugging ML pipelines, and rapid validation, covering competencies such as handling delimiters/quoting/encodings, managing missing or malformed fields, identifying defects in data loading/preprocessing/training, and designing tests under a time constraint.

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Question

Given raw text files with noisy formatting, implement a robust parser that outputs structured examples; handle delimiters, quoting/escaping, encodings/Unicode, missing fields, and malformed lines, and describe how you would test it.
In a provided ML project (data loading, preprocessing, training, evaluation), identify and fix three defects (e.g., index off-by-one in tokenization, train/test leakage, incorrect loss reduction, nondeterministic seeding, or shape mismatches). Explain your rapid debugging approach (stack traces, assertions, binary search logging, minimal repros).
Describe how you would validate the fixes under a 60-minute time limit (unit tests, end-to-end run, metrics sanity checks, and regression guards).

Debug ML pipeline and build text parser

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