Serving frontier LLMs at low latency and high throughput for Cohere's Model Serving team

Cohere's Model Serving team runs the AI platform that delivers Cohere's large language models through production API endpoints. This Staff-level infrastructure role owns the Kubernetes-based, GPU-backed serving stack across multi-cloud environments, balancing latency, throughput, and availability for enterprise customers.

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What this interview tests

Designing highly-available distributed systems on Kubernetes with GPU workloads
Multi-cloud/hybrid production infrastructure (GCP, Azure, AWS, OCI, on-prem)
Inference serving tradeoffs: latency, throughput, availability
Accelerator (GPU/TPU) performance characteristics
Compute/storage/network cost management
Production Linux troubleshooting at scale

Common question themes

Design a highly available, low-latency LLM inference serving system on Kubernetes with GPU nodes

How do accelerator characteristics change your latency/throughput tuning decisions

Walk through a production incident you troubleshot in a complex Linux distributed environment

How would you approach a customer-specific deployment without destabilizing the shared serving platform

Experience running multi-cloud or hybrid infrastructure and tradeoffs you hit

Cost management strategies for GPU compute/storage/network at scale

How candidates describe it

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

LinkedIn · Staff Software EngineerNo offer

LinkedIn Staff Software Engineer Interview: Two Onsite Loops and a Final Reject

A candidate interviewed for a Staff Software Engineer role at LinkedIn's Sunnyvale office, going through two phone interviews and a six-round onsite loop that mixed leadership and craftsmanship questions with coding and system design problems. After the hiring committee decided the candidate was not a match for the Staff level, the candidate returned for a shorter, two-round onsite loop evaluated at the Senior Software Engineer level, which also ended without an offer.

Interviewed July 2018 · Sunnyvale, CA

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

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