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

1. Problem statement and why it matters (impact, users, business/scientific value)
2. Related prior work (2–4 key references and how they fall short)
3. Your novel contributions (what is new and why it works)
4. Methodology (core idea, model/algorithm, training procedure)
5. Experimental setup
   • Datasets and preprocessing
   • Metrics and evaluation protocol
   • Baselines and how you chose them
   • Hardware/compute budget and reproducibility details
6. Key results (with numbers), plus ablations and sensitivity analyses
7. Limitations and failure cases (with concrete examples)
8. Your individual impact (ownership, decisions, lines of code, experiments)
9. Collaboration and timeline (team roles, milestones)
10. What you would do differently and next steps

Expectations

• Use 6–8 slides or a structured narrative; keep a tight arc from problem → evidence → impact.
• Quantify improvements and trade-offs. Be explicit about assumptions and risks.
• Avoid confidential details; use public analogs when needed.