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AI Security

Interview question · LLM Application Security

What security and privacy issues come with fine-tuning a model on customer data?

Fine-tuning moves data from a database you can query and delete into weights you cannot. The scored answer covers memorisation, tenant separation, poisoning and the deletion problem.

mediumNewPreparation tags: OpenAI, Databricks, SnowflakeUpdated Nov 2026

Fine-tuning moves data from a database you can query and delete into weights you cannot. The scored answer covers memorisation, tenant separation, poisoning and the deletion problem.

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What would you say before reading the answer?

  1. 01 State the assumptions your answer depends on.
  2. 02 Explain the mechanism and choose a control.
  3. 03 Name a condition that would change your decision.

The worked answer includes an approach, scoring criteria and follow-up questions. Compare the reasoning with your own.

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What if · the follow-ups in this answer

The answer works through 6 follow-ups like an interviewer would

A company wants to fine-tune a model on two years of customer support tickets to make its assistant sound more like its best agents.

  1. What risks come with this data?
  2. What if you scrub personal data before training?
  3. What must be settled before using the data at all?
  4. What if a customer later asks for their data to be deleted?
  5. What if the goal is only tone and style?
  6. What process would you set?

Each rung has a nudge, a model answer, the principle that carries over and the weak answer to avoid. Premium opens every answer and ladder.

UP NEXT ON YOUR JOURNEY
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