ML Project Overview and Deep Dive (HR Screen)
Context
You are interviewing for a Machine Learning Engineer role. Provide a concise, structured overview of your primary ML project and briefly summarize one or two other major projects. Then, deep-dive into the technologies behind one selected project, explaining choices, trade-offs, and limitations.
Prompts
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Primary ML Project (concise overview)
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Problem definition and business objective
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Data sources and preprocessing
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Model architecture or algorithms
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Training setup (loss, sampling, hardware, orchestration)
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Evaluation metrics (offline and online/A-B)
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Measurable outcomes/impact
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Other Projects (1–2 summaries)
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Objective and high-level approach
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Deep Dive (choose one project)
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Key technologies/frameworks for: data pipeline, model training, deployment/serving, infrastructure
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Why these were chosen over alternatives
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Trade-offs and limitations