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Build an Embedding-Based Semantic Search for a Legal-Document Corpus

FreeVerified credential3 weeksIntermediate

Overview

What this challenge is about.

Build an Embedding-Based Semantic Search for a Legal-Document Corpus. Intermediate challenge in code. Writing production code that solves real engineering pr...

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Build a semantic-search service that beats the keyword baseline on recall-at-10 and ships as a hybrid architecture.

This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.

When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."

Earning criteria — what you'll demonstrate

  • Use pre-trained sentence-transformers for cross-lingual semantic search
  • Compare semantic vs keyword retrieval with proper IR metrics
  • Design hybrid retrieval architectures with reranking
  • Translate evaluation results into production architecture decisions

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Machine Learning (CS Elective)

Master · General Studies

Strong alignment

This challenge maps to Machine Learning (CS Elective) at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.

One more thing

You can put a credential on your CV by Friday.

Build an Embedding-Based Semantic Search | Ewance Challenge