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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4 jobs · 3 companies · last seen 19 August 2026

There are currently 4 open roles in Berlin that mention Qdrant, posted by 3 companies. It frequently pairs with Python, LLM, Vector Databases. Seen most in Leadership (1% of their roles) and AI/ML (1% of their roles).

Frequently asked questions

How many Qdrant jobs are available in Berlin right now?

There are currently 4 open roles in Berlin that mention Qdrant, 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 Qdrant?

Companies currently listing the most Qdrant roles include: Flip, Constructor, Team Passerelle.

What skills pair well with Qdrant?

Employers who ask for Qdrant also frequently require: Python (100%), LLM (100%), Vector Databases (100%), Azure (75%), Kubernetes (75%).

In which Berlin job roles is Qdrant most in demand?

Based on current listings, Qdrant appears most in: Leadership (1%), AI/ML (1%) roles.