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A.10 Job Search Preparation Checklist

Job search preparation funnel diagram

AI job portfolio storyline map

Job preparation is not “learn everything first.” It is turning learning traces into projects other people can understand.

Pick one target role first​

RoleWhat matters mostPrepare
AI / Algorithm EngineerModel understanding, training, evaluationML/DL projects, metrics, experiments
LLM Application EngineerRAG, Agent, backend, product loopComplete app, API design, logs, evaluation
Data Analyst / Data ScientistSQL, statistics, visualization, modelingAnalysis reports and business explanations
AI Product / Technical ProductScenario judgment, requirements, evaluationProduct proposal, metrics, trade-offs

Do not prepare for every direction at once.

Project story format​

Use this structure in resume, README, and interviews:

Target role:
User problem:
Input and output:
Baseline:
Technical solution:
Evaluation result:
Failure case:
What I improved:

Weak:

Used Python and LangChain to build a knowledge base Q&A system.

Stronger:

Built an enterprise knowledge base Q&A system with document chunking, vector retrieval,
permission filtering, and cited answers; created an evaluation set to compare chunking
strategies and reduce false retrievals.

Repository checklist​

  • README
  • How to run
  • Project structure
  • Example input and output
  • Screenshots or demo images
  • Metrics or evaluation method
  • Known issues and next steps

Someone opening the repo should understand the project in 3 minutes.

Interview questions to prepare​

  • Why did you choose this solution?
  • What baseline did you compare against?
  • What failed?
  • How did you evaluate the result?
  • If production breaks, what do you check first?

Four-week sprint​

WeekFocus
1Choose target role and select 2-3 projects
2Improve README, screenshots, run instructions, resume wording
3Practice project explanation and fundamentals
4Apply, record questions, improve projects from feedback