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Deepgram Interview Questions

The questions to prepare for Deepgram interviews, across all roles. Questions from real interview reports rank first. Updated weekly.

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1
CodingStart here. 4 questions · ~36 min
2
Execution4 questions · ~36 min
Prioritize Across Competing Data ProjectsEasy

Explain how you prioritize across multiple concurrent data engineering projects with competing stakeholder needs and limited capacity.

Trade-offsRoadmappingScope ManagementDeepgram
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3
Machine Learning4 questions · ~36 min
Supervised vs Unsupervised LearningEasy

Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.

Unsupervised LearningFeature EngineeringBias-Variance TradeoffDeepgram
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4
System Design4 questions · ~36 min
Design Feature Drift Monitoring SystemHard

Design a production ranking system with robust feature drift monitoring across batch and real-time features at high QPS.

Feature StoreFeature DriftModel ServingDeepgram
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5
Product Sense4 questions · ~36 min
Approach New Feature DesignMedium

A structured approach for designing a new feature in an existing product, from user need to MVP and success criteria.

Feature PrioritizationUser NeedsUse CasesDeepgram
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6
Metrics4 questions · ~36 min
Measure Team Operating EffectivenessMedium

Define a practical KPI set for judging whether an engineering team is operating effectively.

KPIsLeading IndicatorsDiagnosisDeepgram
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7
More topics26 questions · ~232 min
Calculate 30-Day User RetentionHard
Practice

Use CTEs, joins, and date filtering to calculate 30-day retention by signup cohort from login and feature usage data.

Window FunctionsDate FunctionsAggregationsDeepgram
Improve Model AccuracyMedium

Approach for improving a model's accuracy by checking errors, features, and tuning choices.

Hyperparameter TuningCross-ValidationAccuracyDeepgram
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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 min
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