PREP FOR A SPECIFIC LOOP
Interview prep by company
Targeting one company? Each page covers how it hires, what its loop tests, and the questions that map to it. We group honestly by whether the company runs a true AI infrastructure engineer program.
41 companies·18 AI infra programs·updated for 2026
Frontier model labs
7They train the largest models themselves, so the interview is about making a very large run go fast and survive its own failures.LOOP LEANS ON: Training and inference performance, GPU efficiency, distributed failure handling
Hyperscalers and GPU clouds
12They rent capacity to everyone else, so the interview is about fleets, tenants and the physical plant rather than any single model.LOOP LEANS ON: Fleet scale, schedulers, networking, capacity, reliability
Chip and platform vendors
7They build the silicon and the software that drives it, so depth in the team's own domain outranks breadth almost everywhere.LOOP LEANS ON: Microarchitecture, kernels, compilers, interconnect, benchmarking
AI infrastructure scale-ups
9They sell the layer between a model and a product, so the interview is about serving abstractions, multi-tenancy and unit economics.LOOP LEANS ON: Serving and training platforms, multi-tenancy, cost per token, orchestration
ML platforms at product companies
6The model serves a product that would exist without it, so the interview weights platform, data and reliability over raw GPU depth.LOOP LEANS ON: ML platform, data infrastructure, serving reliability, developer experience