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Search Relevance Engineer Jobs (NOW HIRING)

NewsMesh

$170K - $230K/yr

... developers and, increasingly, by AI agents that discover and pay for it on their own. We are a ... Design and tune search relevance over a large, constantly changing corpus * Own evaluation: define ...

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$37K

$87.2K

$136.5K

How much do search relevance engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for search relevance engineer in the United States is $87,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,500.00 and $97,500.00 per year, depending on experience, location, and employer.

What is a search relevance engineer?

A Search Relevance Engineer is a specialist who focuses on improving the quality and accuracy of search results within search engines or website search functionalities. Their main goal is to ensure users find the most relevant information based on their queries by fine-tuning algorithms, analyzing search data, and implementing features like ranking signals, synonyms, and personalization. They work closely with data scientists, product managers, and software engineers to continually test and optimize search systems. By enhancing search relevance, they help improve user satisfaction and engagement.

How does a search relevance engineer typically collaborate with data scientists and product managers to improve search results?

As a Search Relevance Engineer, you’ll work closely with data scientists to analyze user behavior and search data, identifying patterns that inform ranking algorithms and relevance improvements. Collaboration with product managers is also essential, as they help define business goals and user requirements, ensuring that your technical solutions align with product objectives. Regular cross-functional meetings, joint brainstorming sessions, and iterative feedback cycles are common practices, fostering a highly collaborative environment where technical and strategic perspectives come together to enhance the search experience.

What are the key skills and qualifications needed to thrive as a search relevance engineer, and why are they important?

To thrive as a Search Relevance Engineer, you need a solid understanding of information retrieval, natural language processing (NLP), and machine learning, typically supported by a degree in computer science or a related field. Experience with search platforms like Elasticsearch or Solr, as well as proficiency in programming languages such as Python or Java, are commonly required. Strong analytical thinking, collaboration, and effective communication skills help you work with cross-functional teams and interpret user intent. These skills and qualities are essential for building search systems that deliver accurate, relevant results and significantly improve user satisfaction.

What are popular job titles related to Search Relevance Engineer jobs?

For Search Relevance Engineer jobs, the most frequently searched job titles are:

Infographic showing various Search Relevance Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $87,220 per year, or $41.9 per hour.

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NewsMesh
See more jobs at NewsMeshexternal

$170K - $230K/yr

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Posted 8 days ago

Job description

Our search runs over a corpus that changes every minute. Your job is to make it fast, make it relevant, and make the improvement measurable. That spans index design, query understanding, ranking, and the evaluation work that separates a real gain from a convincing demo.

About NewsMesh

NewsMesh turns the world's news into clean, structured, real-time data. We ingest thousands of sources continuously, enrich every article with category, topics, people, and country relevance, and serve it through an API used by developers and, increasingly, by AI agents that discover and pay for it on their own. We are a small, senior team, and the work is measured by one thing: whether the data is right, current, and easy to use.

What you'll do
  • Design and tune search relevance over a large, constantly changing corpus
  • Own evaluation: define precision and recall, measure honestly, improve deliberately
  • Improve entity and topic extraction so filters stay trustworthy
What we look for
  • Experience with production search (Typesense, Elasticsearch, a vector DB, or similar)
  • Solid information-retrieval fundamentals
  • Rigorous about evaluation, not just shipping a model
  • Comfortable in Python and working with large datasets
  • Experience with embeddings, ranking, or learning-to-rank
  • Worked on dedup, clustering, or entity resolution
Compensation

Depending on experience, the expected pay range is $170K–$230K.

What we offer
  • Competitive pay, in the range listed above
  • Remote across the US
  • Real ownership: you will ship work customers depend on
  • A small, senior team with high standards and little process
How we hire

We read every application. If there is a fit, expect a short intro call, a practical exercise rooted in the kind of work you would actually do, and a few conversations with the people you would work with. A link to something you have built beats a resume.

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