Top 22
Prep plan
Updated weekly · Last refresh Aug 30

Optum Machine Learning Engineer Interview Questions

The questions to prepare for a Optum Machine Learning Engineer interview. Questions from real interview reports rank first. Updated weekly.

22questions
~3htotal time
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1
CodingStart here. 3 questions · ~27 min
Custom Loss Without Deep LibrariesMedium
Practice

Implement numerically stable weighted binary cross-entropy from logits and return its loss and gradients.

functionsTestingpythonOptum
Fuzzy Duplicate Patient RecordsHard

Tests SQL proficiency and your ability to implement fuzzy matching logic for patient identity resolution.

deduplicationsqlOptum
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2
System Design6 questions · ~53 min
Hybrid EHR and Notes ModelingHard

Tests your ability to design multimodal ML pipelines combining EHR features and clinical text.

Feature StoreRetrievalNLPOptum
Real-Time Feature Store for Wait TimesHard

Tests your architecture choices for low-latency features and reliability in real-time healthcare predictions.

Feature StoreFeature DriftModel ServingOptum
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3
Machine Learning4 questions · ~35 min
Bias-Variance and Cross-ValidationMedium

Tests your conceptual mastery of generalization and your ability to apply cross-validation in practice.

Cross-ValidationBias-Variance TradeoffDeep LearningOptum
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4
Behavioral & Leadership5 questions · ~44 min
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5
More topics4 questions · ~35 min
Testing Demographic BiasHard

Tests your ability to design statistical validation for fairness and bias detection in healthcare ML.

BiasHypothesis TestingStatistical SignificanceOptum
Transformer for Clinical NotesHard

Tests your deep understanding of transformers and your ability to adapt attention to clinical text use cases.

transformersOptum
Streaming Wearable Ingestion PipelineHard

Tests your data engineering design for streaming ingestion at scale relevant to Optum’s health technology.

Stream ProcessingAutomationingestionOptum
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The finish line: interview-readyComplete all 22 questions to finish this plan.