Build a Candidate Search System
Problem Statement
Design and implement an end-to-end candidate search system for recruiting purposes.
Input
Each search request will consist of a job posting, which includes:
- Job title
- Job description
- Hard criteria, such as required skills, location constraints, work authorization, minimum years of experience, education, and availability.
You will have access to a candidate database. Each candidate profile in this database may contain:
- Structured fields: e.g., location, skills, years of experience, and availability.
- Unstructured text: e.g., resumes, work history, project descriptions, and notes.
Output
The system must return the 10 best-matching candidates for the given job posting.
Requirements
- Hard Criteria Enforcement: Correctly enforce all specified hard criteria whenever possible.
- Relevance Ranking: Rank candidates based on their overall relevance to the job posting.
- Hybrid Matching: The system must handle both structured filtering based on explicit fields and semantic matching over unstructured candidate text.
- End-to-End Implementation: The solution should be an end-to-end working implementation, capable of being evaluated by an automated endpoint.
- Quality Iteration: The system should allow for using evaluation results to debug and iterate on search quality.
- Architectural Explanation: Be prepared to explain the use of AI tools, the design of the retrieval and ranking pipeline, and how quality issues were diagnosed and resolved.
AI interview prep
Core dilemma
Balancing the precision and recall of semantic search over unstructured text with the strict enforcement of hard, structured criteria, all while ensuring low latency for a real-time search experience and scalability for a large candidate pool.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Build a Candidate Search System
Problem Statement
Design and implement an end-to-end candidate search system for recruiting purposes.
Input
Each search request will consist of a job posting, which includes:
- Job title
- Job description
- Hard criteria, such as required skills, location constraints, work authorization, minimum years of experience, education, and availability.
You will have access to a candidate database. Each candidate profile in this database may contain:
- Structured fields: e.g., location, skills, years of experience, and availability.
- Unstructured text: e.g., resumes, work history, project descriptions, and notes.
Output
The system must return the 10 best-matching candidates for the given job posting.
Requirements
- Hard Criteria Enforcement: Correctly enforce all specified hard criteria whenever possible.
- Relevance Ranking: Rank candidates based on their overall relevance to the job posting.
- Hybrid Matching: The system must handle both structured filtering based on explicit fields and semantic matching over unstructured candidate text.
- End-to-End Implementation: The solution should be an end-to-end working implementation, capable of being evaluated by an automated endpoint.
- Quality Iteration: The system should allow for using evaluation results to debug and iterate on search quality.
- Architectural Explanation: Be prepared to explain the use of AI tools, the design of the retrieval and ranking pipeline, and how quality issues were diagnosed and resolved.