Twilio
Senior
Lead Twilio's Trust Intelligence Platform team building real-time ML risk models across messaging, voice, and email
Twilio is hiring a Senior Engineering Manager to lead the Traffic Intelligence org's ML and data engineering team, which builds real-time risk-prediction models and pipelines to detect fraud and unwanted communications across all Twilio channels. This interview evaluates hands-on ML systems depth (PyTorch/TensorFlow, Kafka/Spark, AWS SageMaker) combined with people leadership and cross-functional roadmap execution at executive visibility.
Step into this interview
Free · a live voice mock calibrated to this exact role
What this interview tests
- Production ML systems: shipping, monitoring, and maintaining models at scale
- Real-time data pipelines (Kafka, Spark, batch + streaming)
- Cloud ML infra (AWS SageMaker, EKS/ECS) and observability (Datadog, Grafana)
- Cross-functional partnership with Fraud/Compliance and Data Analytics teams
- On-call ownership and incident response for critical risk-decisioning systems
- Managing and mentoring ML/data engineers, roadmap planning with Product
Common question themes
Tell me about an ML model you shipped to production and kept healthy — how did you monitor for drift and reduce operational toil?
Describe a real-time or near-real-time data pipeline you built — what was the tech stack and where were the bottlenecks?
How would you translate a new fraud vector, discovered by an operations team, into a concrete model or pipeline change?
Walk me through an incident in a risk/fraud-detection system — how did you triage, mitigate, and prevent recurrence?
How do you balance long-term ML platform investment against urgent fraud/compliance asks?
How do you mentor engineers with mixed ML and data engineering backgrounds?
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