Deep technical project narrative and lessons learned Questions
Prepare detailed discussion of a significant project: the problem, your approach, technical decisions and trade-offs, challenges and how you overcame them, outcome, and what you learned. Practice explaining this clearly in 10-15 minutes, leaving time for questions.
MediumSystem Design
0 practiced
Describe your deployment pipeline and MLOps practices: CI/CD for models, containerization, model versioning, artifact storage, canary or blue-green rollouts, feature flags, health checks, and rollback strategy. Explain how you guaranteed reproducibility and safe rollouts with minimal user impact.
MediumTechnical
0 practiced
Your company has a tight budget for inference GPU instances. Explain practical strategies to reduce inference cost: model distillation, quantization, batching, serverless or preemptible instances, tiered serving (small vs large models), caching common responses, and trade-offs you would accept for lower cost. Provide rough expected savings and performance impacts.
HardTechnical
0 practiced
Discuss a time you discovered fairness or bias issues in a model. Explain how you detected the bias (metrics and subgroup analysis), the mitigation approach you chose (data collection, relabeling, reweighting, constraints, post-processing), validation of mitigation, and any trade-offs with accuracy or business KPIs.
MediumTechnical
0 practiced
Explain how you made model predictions interpretable for non-technical stakeholders. Describe the tools or techniques you used (SHAP, LIME, attention-visualizations), examples of explanations you produced for specific predictions, and any limits or caveats you communicated about those explanations.
MediumTechnical
0 practiced
If you were asked to hire for the team after completing the project, what roles and skills would you prioritize (ML engineers, data engineers, MLOps, research scientists)? Describe interview criteria, example technical exercises or take-home assignments, and a 30/60/90 day onboarding plan to ensure new hires are productive quickly.
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