Rivac LabsSearch Relevance Engineer
Search that returns technically-matching but practically-useless results quietly drives users away long before anyone files a complaint about it. We work on query understanding, embedding strategy, and ranking evaluation to make search results actually match user intent, using real query logs and click data rather than assumptions about what users want. This is for any product where internal search, product search, or document search is underperforming and it's hurting conversion, support load, or user retention. You get a ranking system measured against real queries with a defined relevance metric, not a search box that just happens to return something.
How We’d Approach This
A clear, staged plan — not a black box
- 1
Analyze real query logs and click-through data to diagnose where current search relevance is failing users.
- 2
Build a pilot ranking change — embeddings, query rewriting, or re-ranking — against a query evaluation set.
- 3
Review relevance metrics and sample results with your team before rolling the change out broadly.
- 4
Deploy the tuned ranking with the evaluation set in place to catch regressions on future changes.
What You Get
Deliverables from this engagement
- Tuned search ranking pipeline with measured relevance improvement
- Query evaluation set for ongoing relevance testing
- Embedding or ranking configuration documented
- Dashboard tracking search relevance metrics over time
Six Ways We Could Architect This
Different engagement, different build — pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start — scoped small enough to prove itself before you commit to anything bigger.
Talk to us about Search Relevance EngineerMost engagements like this start as a $500–$2,500 pilot — see full pricing.