Plan and lead a large recommendation project
Company: LinkedIn
Role: Machine Learning Engineer
Category: Behavioral & Leadership
Difficulty: medium
Interview Round: Onsite
You are given a recommendation design problem, but the interviewer focuses on leadership and execution rather than detailed modeling.
Explain how you would:
1) Turn a high-level recommendation idea into an execution plan (milestones, dependencies, risks).
2) Estimate staffing: what roles you need (e.g., MLE, DS, backend, product, design, data engineering) and roughly how many people.
3) Propose a realistic timeline (phased rollout) and how you would coordinate cross-functionally.
4) Define success metrics and how you would run experiments.
5) Handle trade-offs, disagreements, and communication to stakeholders.
Overview: This Behavioral & Leadership question evaluates leadership, execution planning, cross-functional coordination, resourcing, and stakeholder communication skills in the context of machine learning recommendation product development.
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