Describe internship and research projects
Overview
This question evaluates end-to-end ownership, leadership and communication skills alongside technical depth in machine learning systems, including model selection, data pipelines, performance metrics, and scalability.
TikTok
Aug 8, 2025, 12:00 AM
Machine Learning Engineer
Technical Screen
Behavioral & Leadership
0
0
Behavioral/Leadership Prompt: Two Projects (Internship + Research)
Context
You are interviewing for a Machine Learning Engineer role during a technical screen. The interviewer wants concise, structured evidence of end-to-end ownership, technical depth, and measurable impact.
Task
Briefly introduce two projects—one internship and one research. For each project, cover:
- Problem and constraints (business/user goal, scale, latency/memory limits, data availability)
- Your role and ownership (what you personally led/built/decided)
- Key technical decisions and why (model/data/pipeline/metrics; trade-offs)
- Notable challenges and how you addressed them (failure modes, debugging, constraints)
- Measurable results/impact (offline and online metrics, A/B outcomes, latency/throughput)
- One improvement if you had more time (next step, risk you’d retire, or scalability plan)
Keep each project to ~2–3 minutes. Use concrete numbers where possible (e.g., +2.1% CTR, p99 latency 45 ms, AUCPR +0.16).
Solution
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