Jane Street interview questions
Big tech · 1 question reported
- junior 0
- mid 0
- senior 1
These are 1 technical questions candidates reported being asked in Jane Street interviews for AI engineer, ML engineer and applied AI engineer roles, each with a model answer you can say out loud in a minute or two. They cover training: 0 junior, 0 mid-level and 1 senior questions. Every question comes from a public interview write-up that names Jane Street.Updated
Jane Street training and optimisation questions
Model answer
Datasets build windows lazily from contiguous arrays, with input length, horizon and stride in config. Split by time with a gap so no window straddles the boundary, and fit normalisation on training data only.
Reproducibility: seed every RNG, record config, code version and a data hash, and use deterministic kernels where it matters. Distribute with DDP or FSDP and a distributed sampler. Checkpoints hold model, optimizer, scheduler, RNG states and step, written atomically, so resuming is exact. Evaluate with walk-forward backtests per horizon against naive baselines like last value.
Each question comes from a public interview write-up or video that names Jane Street; the answers are ours. Not affiliated with Jane Street.