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Yahoo·Software Engineer·Onsite - Product Sense / Strategy·Senior

SeniorPrefer not to say
Jun 2026

Summary

Yahoo threw a big open-ended resource allocation question at me and I genuinely wasn't sure if there was a right answer or if they just wanted to see how I think.

Questions Asked (1)

Q1

If you had 20 engineers, 100,000 computers, and 3 months, what would you build?

Product StrategySystem DesignAdaptability & Ambiguity
Author's notes

Blanked for a solid few seconds on this one.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the constraints and goals: what does Yahoo need most? Then propose a project that leverages the massive compute and team size, such as a large-scale data processing or machine learning system. Structure your answer by outlining the problem, your solution, and how you'd execute it within 3 months.

Pro tip: Show that you can prioritize impact over novelty: pick a project that directly addresses a Yahoo pain point, like improving ad targeting or search relevance, and explain how you'd measure success.

1. Clarify the scenario

Ask questions to understand the context: Is this for an existing product or a new initiative? What are Yahoo's current challenges? What are the success metrics?

2. Identify high-impact opportunities

Brainstorm areas where 100,000 computers and 20 engineers can make a significant difference, such as large-scale machine learning, data processing, or infrastructure improvements.

3. Choose a project and justify it

Select one project that aligns with Yahoo's business goals, such as a real-time personalization engine or a distributed training platform, and explain why it's feasible and valuable.

4. Outline execution plan

Describe how you'd organize the team, allocate resources, and hit milestones within 3 months, including risk mitigation and iteration.

5. Define success metrics

Specify how you'd measure the project's impact, such as improved click-through rates, reduced latency, or cost savings.

Key Points to Mention

  • Leveraging distributed computing for large-scale data processing or machine learning
  • Aligning the project with Yahoo's core businesses (search, ads, media)
  • Team organization and parallel workstreams to maximize productivity
  • Incremental delivery and quick wins within the 3-month timeframe
  • Scalability and potential for long-term impact
  • Risk management and fallback plans

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.