Scale AI Interview Question Bank

Scale AI's recent engineering loops are practical and implementation-heavy: candidates are expected to write working code under shared-screen conditions, reason about production readiness, and explain prior ML or product work clearly. MLE loops add NumPy-level model implementation, LLM training theory, and paper or project trade-off discussions, while FDE and enterprise roles lean toward customer-facing AI systems.