I went through HF's senior engineering loop earlier this year and the system design round was the part I stressed about most. Wanted to share what it actually looked like because the prep advice online is mostly generic.
I came from a data/ML background, not classic distributed systems, so I was worried they'd want me to design a Kafka cluster or a sharded database from scratch. That's not what happened.
The prompt was something in the space of: design a system that serves model inference at scale. You pick the model type, you talk through the architecture. So it's ML-adjacent system design, which for HF makes total sense.
What they were actually evaluating: Whether you could identify the latency vs throughput tradeoffs for a serving system Whether you had opinions about batching, caching, and queueing at the inference layer Whether you could articulate how you'd monitor and handle failures
They were NOT testing whether you could recite consistent hashing or raft consensus. If that stuff came up naturally fine, but it wasn't the point.
One thing that helped me: I had shipped something on top of the Transformers library for a previous job, and being able to reference that concretely gave me a lot to work with. "Here's what I built, here's where it broke at scale, here's how I'd redesign it" is a great structure.
For senior L5-equivalent roles I'd guess they care a lot about: Systems thinking at the ML layer, not just the infra layer Opinions backed by real tradeoffs you've encountered The ability to say "I don't know" and then reason through it
I got the offer, so something worked. Happy to answer specific questions.