- Length
- 60 min
- Format
- One problem in three to five growing parts filling the hour, usually in CoderPad; ML roles get a Colab notebook with autocomplete off
- They grade
- Working, tested code and sound handling of edge cases; the first two or three parts done cleanly is the usual bar
- AI use
- No AI assistants or autocomplete; documentation is fine
- Heads-up
- Problems are framed as real work: simulations, a memory allocator, an IP range iterator, a credits ledger. A finished, tested solution beats an unfinished clever one. ML and research roles often get ML coding instead (find the bugs in a small transformer, vectorize a NumPy loop), and some infra loops use a 75-minute systems coding round on concurrency.