A vector database, vector store or vector search engine is a database that stores and retrieves embeddings of data in vector space. Vector databases typically implement approximate nearest neighbor algorithms so users can search for records semantically similar to a given input, unlike traditional databases which primarily look up records by exact match. Use-cases for vector databases include similarity search, semantic search, multi-modal search, recommendations engines, object detection, and retrieval-augmented generation (RAG).

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3 jobs · 3 companies · last seen 22 September 2026

There are currently 3 open roles in Berlin that mention pgvector, posted by 3 companies. It frequently pairs with Python, LLM, Vector Databases. Seen most in genAI/LLM/Agentic AI (1% of their roles) and AI/ML (1% of their roles). Across those roles, 100% list it as required and 0% as nice-to-have.

Frequently asked questions

How many pgvector jobs are available in Berlin right now?

There are currently 3 open roles in Berlin that mention pgvector, posted by 3 companies. The board is refreshed multiple times a day — more frequently during Berlin working hours — so new roles can appear throughout the day.

Which companies in Berlin are hiring for pgvector?

Companies currently listing the most pgvector roles include: Camunda, Constructor, Actian.

What skills pair well with pgvector?

Employers who ask for pgvector also frequently require: Python (100%), LLM (100%), Vector Databases (100%), Agentic AI (100%), Google Cloud (67%).

In which Berlin job roles is pgvector most in demand?

Based on current listings, pgvector appears most in: genAI/LLM/Agentic AI (1%), AI/ML (1%) roles.