10–15 Minute Research Project Overview (Technical Screen)
Context
You are interviewing for a Machine Learning Engineer role. Prepare a concise, technical 10–15 minute walkthrough of your most impactful research project.
Cover the following, in order
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Problem statement and why it matters (impact, users, business/scientific value)
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Related prior work (2–4 key references and how they fall short)
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Your novel contributions (what is new and why it works)
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Methodology (core idea, model/algorithm, training procedure)
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Experimental setup
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Datasets and preprocessing
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Metrics and evaluation protocol
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Baselines and how you chose them
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Hardware/compute budget and reproducibility details
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Key results (with numbers), plus ablations and sensitivity analyses
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Limitations and failure cases (with concrete examples)
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Your individual impact (ownership, decisions, lines of code, experiments)
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Collaboration and timeline (team roles, milestones)
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What you would do differently and next steps
Expectations
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Use 6–8 slides or a structured narrative; keep a tight arc from problem → evidence → impact.
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Quantify improvements and trade-offs. Be explicit about assumptions and risks.
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Avoid confidential details; use public analogs when needed.