Entity Resolution & Search Engineer
San Francisco, CA (Remote)
$175K/yr – $240K/yrFull time
Posted 1 day ago
Job Description
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Entity Resolution & Search Engineer
Location San Francisco, CA or Remote (US) Type Full-time Compensation $175K–$240K
About The Role
Public information is written a thousand different ways, and the same entity shows up under a hundred names. Your job is to decide when two things are the same thing, resolve them into one clean record, and make the result fast and accurate to search. This work ties our platforms together across news, places, government, and markets.
About NimbleFig
NimbleFig is a data company. We acquire and operate data platforms that turn the world's public information into clean, structured, real-time data for people and machines, across news, places, government, and markets. Most of it is written for human eyes, scattered across millions of sources, and out of date the moment it ships. Our job is to make each part of that record complete, current, and ready to query. 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
Depending on experience, the expected pay range in California is $175K–$240K.
What we offer
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.
Apply for this role
Entity Resolution & Search Engineer
Location San Francisco, CA or Remote (US) Type Full-time Compensation $175K–$240K
About The Role
Public information is written a thousand different ways, and the same entity shows up under a hundred names. Your job is to decide when two things are the same thing, resolve them into one clean record, and make the result fast and accurate to search. This work ties our platforms together across news, places, government, and markets.
About NimbleFig
NimbleFig is a data company. We acquire and operate data platforms that turn the world's public information into clean, structured, real-time data for people and machines, across news, places, government, and markets. Most of it is written for human eyes, scattered across millions of sources, and out of date the moment it ships. Our job is to make each part of that record complete, current, and ready to query. 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
- Build and improve entity resolution and record linkage across our platforms
- Design and tune search relevance across large, constantly changing corpora
- Own evaluation: define precision and recall, measure honestly, and improve deliberately
- Grow and maintain the entity graph that connects data across domains
- Turn fuzzy, ambiguous matching problems into systems that hold up in production
- Experience with entity resolution, record linkage, dedup, or search (lexical or vector)
- Solid information-retrieval or applied-ML fundamentals
- Rigorous about evaluation, not just shipping a model
- Comfortable in Python and working with large datasets
- Built or tuned a production search system (Elasticsearch, a vector DB, or similar)
- Experience with embeddings, ranking, or learning-to-rank
- Familiarity with knowledge graphs or graph data
Depending on experience, the expected pay range in California is $175K–$240K.
What we offer
- Competitive pay, in the range listed above
- Remote across the US, or in person in San Francisco
- Real ownership: you will ship work that customers depend on
- A small, senior team with high standards and little process
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.
Apply for this role
Salaries
Posted range
$175K/yr – $240K/yr
Taken straight from the job posting.
