Neuronify

Vector search (vector databases)

Finding the items whose embeddings are closest to a query’s embedding — the retrieval step behind semantic search and most RAG systems.

Hiring data as of September 20, 2026 · refreshed daily

companies naming it
9 of 47companies naming it
open roles naming it
18open roles naming it
of those based in NYC
9of those based in NYC
pay: under 8 posted ranges
—pay: under 8 posted ranges

What Vector search means

Vector search retrieves items by similarity of meaning rather than by matching keywords. Content is converted to embeddings and indexed; a query is embedded the same way; the index returns the nearest neighbors. A vector database is a store built for that operation at scale — Pinecone, Weaviate, Qdrant, and pgvector are common choices, and Elasticsearch supports it alongside keyword search.

In practice the best results usually come from hybrid retrieval, which combines vector similarity with keyword matching and then reranks. Pure vector search misses exact identifiers such as part numbers and names, which is often exactly what enterprise users type.

Vector search in New York job posts

9 of the 47 New York AI companies we track name Vector search in at least one open role today, across 18 postings. 9 of those are based in New York; the rest are remote or in the companies’ other offices.

This is engineering vocabulary: 61% of the postings that name it are Engineering roles.

How to read it

Shows up with RAG in the same postings and points to a product built on retrieval. If the posting also names a specific vector database, the choice has been made; if it names only the concept, you may be the one making it.

What these roles pay

Not enough data to publish. We need at least eight distinct posted salary ranges on New York roles naming Vector search before showing a median, and today there are fewer. For posted pay by function and seniority across the whole market, use the NYC salary calculator or the NYC AI engineer salary guide.

Trend

We began extracting this term from posting text on September 20, 2026. Job descriptions disappear when a role is filled, so the series cannot be backfilled; a trend line appears here once a week of data exists.

Who names it

Open roles naming Vector search, by company.

  • AlphaSense7
  • Pinecone4
  • April1
  • Clay1
  • EvolutionIQ1
  • Headway1
  • Kustomer1
  • Maven Clinic1
  • Patlytics1

Which roles

The same postings, by function and by seniority.

  • Engineering11
  • GTM6
  • Product1
  • Staff/Principal9
  • Mid7
  • Manager1
  • Senior1

Named alongside Vector search

Terms that appear in the same postings far more often than chance would put them there. The number is how many of the 9 companies pair the two.

Open roles naming Vector search

A sample from today’s data, New York roles first and one per company before any repeats. Links go to the employer’s own posting. For the full market, see AI jobs in NYC.

How this is counted

Every day we read the open roles on the public job boards of the New York AI companies in our coverage — the NYC AI 100 and the AI in NYC Show roster. This term is matched against each role’s description after removing the text a company repeats across its postings, so an “About us” paragraph cannot tag every role the company has open. A vendor’s own postings never count toward its own name.

The figure means named in a job posting. It does not mean used in production, and a “nice to have” counts the same as a requirement. Companies are the headline number because posting counts are dominated by whichever few employers are hiring hardest this month.

Full method, including the pay rules, is on the glossary index; the underlying series is the NYC AI Hiring Index.

Vector search — common questions

What does Vector search mean in an AI job posting?

Finding the items whose embeddings are closest to a query’s embedding — the retrieval step behind semantic search and most RAG systems. Shows up with RAG in the same postings and points to a product built on retrieval. If the posting also names a specific vector database, the choice has been made; if it names only the concept, you may be the one making it.

How many New York AI companies are hiring for Vector search?

As of September 20, 2026, 9 of the 47 New York AI companies we track name Vector search in the description of at least one open role, across 18 postings (9 based in New York). The count refreshes daily from the companies’ own job boards.

What do roles that ask for Vector search pay in New York?

We do not publish a pay figure for Vector search yet. Fewer than eight New York postings naming it carry a distinct posted salary range, and below that number a median says more about two or three employers than about the market.

Which skills are asked for alongside Vector search?

In the same postings, the terms most distinctively paired with Vector search are Embeddings, RAG, Elasticsearch, MLOps, Tool use. We rank pairings by how much more often they appear together than apart, so near-universal terms such as Python do not crowd out the informative ones.

Need someone who has actually shipped this?

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