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类型:qbank
Discuss a prior project, paper, or research-style artifact in enough depth to justify technical choices and fit with the target team. MLE loops can use a formal presentation; HM screens use a conversational project deep dive.
Requirements
Choose a previous project or paper that aligns with the target team.
Be ready to explain:
The problem and why it mattered.
Your ownership and concrete contribution.
Why the project was challenging.
Architecture or model choices.
Alternatives considered and why they were not chosen.
Trade-offs and limitations.
What you would change if doing it again.
MLE presentation variant:
Pick a previous paper to present.
Justify the choice of model architecture.
Explain why another model architecture was not used.
Keep the presentation around 30-45 minutes depending on round format.
HM screen variant:
Project deep dive.
Why Scale AI.
Whether the project aligns with the team and work direction.
Presentation variant for a general SWE audience:
Explain domain-specific concepts in accessible terms.
Make the narrative metrics-driven rather than relying on domain familiarity.
Notes
This round can look casual but is still technical. Generic project summaries are weak; prepare decision-level detail.
Strong answers connect business or research context to the technical choice: why this model, this data pipeline, this evaluation, or this system boundary.
The interviewer may be a generalist SWE even for a highly specialized project, so the slides must teach the necessary domain context without losing technical depth.
For LLM-facing teams, choose a project involving post-training, evaluation, RAG, agents, model serving, data quality, or customer-facing AI integration if you have one.
Preparation
Prepare two projects: one ML/LLM-heavy and one systems/product-heavy, so you can adapt to interviewer focus.
Draw the architecture or experiment flow before the interview and rehearse a 5-minute overview plus a 25-minute deep dive.
For every major choice, write one rejected alternative and the reason it lost.