Apply AI/ML to fault-tolerance and reliability across Google's global data center fleet

Senior software engineer role building AI/ML models that predict, detect, and mitigate hardware and software faults across Google's entire infrastructure fleet, including ML TPUs. Requires 8 years of software development experience with 5 years specifically in ML infrastructure/design, analyzing petabytes of telemetry to improve reliability at hyperscale.

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Likely format

Google SWE loop: phone screen(s) covering coding and ML/infra domain knowledge, followed by onsite rounds spanning coding, ML system design, and Googleyness/leadership behavioral interviews.

What this interview tests

ML model design for fault prediction/anomaly detection at fleet scale
Working with large-scale telemetry and operational data pipelines
ML infrastructure: model deployment, evaluation, fine-tuning, debugging
Cross-functional partnership with hardware designers and SREs
Technical leadership: setting direction, translating findings for executives

Common question themes

Design an ML system to predict hardware faults from fleet telemetry data

How do you evaluate a model when failure events are rare/imbalanced

Describe a project applying ML to an infrastructure reliability problem

How do you productionize and monitor an ML model that others depend on operationally

Explain a complex technical reliability finding to a non-technical stakeholder

How candidates describe it

Real Software Engineer interview stories — retold from candidates' public write-ups, with sources.

Google · L3 Software EngineerOffer

Google L3 software engineer interview: phone screen, four coding rounds, and the Googleyness round

A candidate with two years of experience went from recruiter outreach to offer over about four months. The onsite was four 45-minute coding rounds — three of them featuring binary trees — and one round turned into a 25-minute chain of follow-ups about approximating an optimal solution at scale.

Interviewed June 2020 · Bangalore, IN

Google · L4 Software EngineerNo offer

Google L4 Software Engineer Interview: Eight Rounds, No Offer

An L4 Software Engineer candidate went through two phone screens, three onsite rounds, a culture conversation, and a team-matching call with a Google hiring manager, then watched the process stall for about a month and a half over a tightened experience requirement before an added extended round ended without an offer.

Interviewed February 2024 · Not specified

Google · L5 Software EngineerNo offer

Google L5 software engineer interview: phone screening, three onsite rounds, system design, and a late rejection

A candidate interviewing for an L5 role went through a phone screening, three onsite coding rounds, a mobile system design round, and a Googleyness and Leadership round. Two of the four technical rounds went poorly by the candidate's own assessment, and after roughly two months of silence the recruiter reported that the role had been closed.

Interviewed January 2023 · Not specified

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