Advanced Deep Learning Interview Questions, issue 4, Mar 25, 2026
The I/O Starvation Trap
Senior ML Engineer interview at Meta, and the interviewer asks:
“You just migrated your team’s deep learning workloads from local hardware to a massive AWS GPU cluster to accelerate training. The expensive instances are successfully spinning, but your training iteration speed has actually flatlined. What is the hidden system bottleneck throttling your pipeline?”
Don’t say: “It’s a network latency issue. We just need to pay for a higher-bandwidth VPC or upgrade to faster compute instances.”
Scaling compute exposes that your pipeline is gated by data throughput, not model execution.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.