SDE 3 / Lead Engineer — Real-World Interview Questions

Target Role: SDE 3 / Lead Engineer at Genentech: Biomedicines
Focus Areas: ML Platform, Infrastructure, LLMOps, System Design, Coding

Resume / Intro Questions

Tell me about yourself.
Describe your work experience as it relates to this role.
Why Genentech: Biomedicines, and why this specific role?
Tell me about a project — what was your role, and how did you coordinate with other engineers?
Do you have any questions before we start?

Which parts of the Drift platform did you lead versus implement?
Who are the customers of this platform?
How would you onboard new customers to the platform?
How do you handle customer support issues?
How many people worked on the platform?
What were the roles of the other engineers on the platform team?
How long did it take to go from zero to the first set of customers?
What customer onboarding issues did you encounter in the beginning?
Give a specific example where a customer disagreed with a feature decision — how did you handle it?
When designing the system, what bad decisions were made?
How far along were you when you noticed the issue, and how did you course-correct?
Collaboration: Tell me about a time you worked with other teams to solve a complex issue.
How did you enforce standardization across multiple teams?
How did you track and control costs in the project?
What were the overall project and resource costs at Amazon?

How did you implement observability for ML training workloads?
Walk me through your experience with ML model training pipelines.
Have you used MLflow or other experiment tracking tools? Describe your setup.
How did you run and manage Kubernetes training workloads?
What Kubernetes deployment types have you worked with?
What other Kubernetes workload types have you used — such as ReplicaSet, DaemonSet, StatefulSet?
What is the difference between Kubernetes liveness, readiness, and startup probes?
How many Kubernetes clusters did you manage?
Did you deploy your own clusters, or did you use managed clusters (e.g., EKS, GKE)?
How much control did you have over the cluster configuration and lifecycle?

Agentic tools — to what extent have you used them in production?
If we allow agents to control data pipelines and tooling autonomously, what problems might we run into?
Have you used Claude Code in VS Code? What was your experience?
Does Amazon Q use Claude under the hood?

Design an ML training platform for protein design researchers — walk through your architecture.
How do you deploy ML models safely using canary releases, validation gates, and rollback strategies?
How do you monitor data drift, model drift, and overall pipeline health in production?
How would you standardize ML workflows for multiple teams with different tooling preferences?

Two Sum — given an array of integers and a target, return the indices of the two numbers that add up to the target.
Write a Python function to deduplicate dataset records from multiple biological sources using a composite key.
Write code to detect duplicates and missing values in a dataset — describe your approach and edge cases.

Last updated: March 2026