Embeddings
Show where Embeddings affected a real decision in the project. Include the implementation, constraint, test or measurement that makes the skill verifiable.
CAREER PROJECT · Intermediate · 1–2 weekends
Semantic Search Engine
Index a real corpus, implement semantic retrieval and compare it with keyword baselines.
EmbeddingsVector searchEvaluationAPIsRanking
WHAT THIS PROJECT PROVES
Make the engineering visible.
This brief is designed as portfolio evidence for a AI Engineer path. The goal is not to claim a hiring outcome; it is to make your implementation, judgment and tradeoffs easier to inspect.
Vector search
Show where Vector search affected a real decision in the project. Include the implementation, constraint, test or measurement that makes the skill verifiable.
Evaluation
Show where Evaluation affected a real decision in the project. Include the implementation, constraint, test or measurement that makes the skill verifiable.
APIs
Show where APIs affected a real decision in the project. Include the implementation, constraint, test or measurement that makes the skill verifiable.
Ranking
Show where Ranking affected a real decision in the project. Include the implementation, constraint, test or measurement that makes the skill verifiable.
BUILD PLAN
Finish the core before expanding the scope.
Use this as a project sequence, not a rigid tutorial. Your stack can change; the evidence should still show what you built, why you built it that way and how you know it works.
Define the scope and success criteria
Turn the brief into a small finishable system. Decide what the core Semantic Search Engine must do, what you will deliberately leave out, and how you will show that it works.
Build the core workflow
Index a real corpus, implement semantic retrieval and compare it with keyword baselines. Keep the first pass focused on the main user or system flow before adding stretch features.
Add engineering proof
Create indexed corpus and search ui/api. Document the decisions, failure states, tests, performance, security or operational tradeoffs that matter for this project.
Ship and package the evidence
Publish the strongest artifacts, including benchmark queries, baseline comparison, latency notes. Make it easy for a reviewer to understand the problem, architecture, tradeoffs and what you personally implemented.
PORTFOLIO PROOF CHECKLIST
Leave artifacts a reviewer can inspect.
A strong project page should make it possible to understand the system without guessing what you personally built.
01
Indexed corpus
02
Search UI/API
03
Benchmark queries
04
Baseline comparison
05
Latency notes
06
A concise README explaining the problem, architecture and tradeoffs
07
A working demo, API example or reproducible run path
08
Evidence of testing, monitoring, performance, accessibility or reliability where relevant
RESUME / PORTFOLIO FRAMING
Describe what you actually did.
Built and evaluated semantic search against keyword baselines using a repeatable relevance benchmark.
Use this as a starting structure, then replace it with your real implementation details, metrics and constraints. Do not claim outcomes you did not measure.
INTERVIEW TALKING POINTS
Be ready to defend the decisions.
These prompts turn the project from a repository link into a technical conversation about judgment, tradeoffs and evidence.
Why did you choose your approach to Embeddings, and what alternative did you reject?
Answer with details from your implementation. Prefer concrete constraints, measurements and alternatives over generic best practices.
Where could Semantic Search Engine fail under real usage, and how would you detect or recover from that failure?
Answer with details from your implementation. Prefer concrete constraints, measurements and alternatives over generic best practices.
How did Vector search affect the rest of the design?
Answer with details from your implementation. Prefer concrete constraints, measurements and alternatives over generic best practices.
What did you measure or test to prove Ranking instead of only claiming it?
Answer with details from your implementation. Prefer concrete constraints, measurements and alternatives over generic best practices.
If you had one more week, what would you improve first and why?
Answer with details from your implementation. Prefer concrete constraints, measurements and alternatives over generic best practices.
STRETCH GOALS
Go deeper only after the core is solid.
Hybrid ranking
Add it only if it strengthens the engineering story instead of delaying a finished, deployable core.
Reranker
Add it only if it strengthens the engineering story instead of delaying a finished, deployable core.
Query analytics
Add it only if it strengthens the engineering story instead of delaying a finished, deployable core.
RELATED PORTFOLIO PROJECTS
Build another signal in the same path.
Choose another project only when it proves a different part of the role instead of repeating the same evidence.
Advanced2–3 weekends
RAG Evaluation Workbench
Build retrieval-augmented generation with repeatable quality evaluation instead of stopping at chat.
LLMsRetrievalEvaluationData pipelinesObservability
Open project brief →Intermediate2 weekends
Support Ticket Triage Assistant
Classify and route support tickets with confidence thresholds, human review and evaluation.
ClassificationLLMsEvaluationHuman-in-loopAPIs
Open project brief →Advanced2 weekends
Document Extraction Pipeline
Extract structured fields from messy documents and evaluate correctness against labeled examples.
OCR/visionStructured outputEvaluationPipelinesValidation
Open project brief →