Andrey Vasnetsov
Co-Founder, CTO at Qdrant
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolAndrey Vasnetsov is a founder and CTO with 12 years of experience building production-grade ML systems and distributed software, currently leading Qdrant, a high-performance open-source vector search engine. He blends hands-on backend and database engineering (Rust, gRPC, REST) with practical ML expertise in vector similarity, metric learning, and self-supervised approaches, preferring simple, usable libraries over academic complexity. Previously he led ML and search teams at Tinkoff and MoBerries, shipping neural-search systems and a platform for rapid model deployment. An active open-source maintainer, he improved Qdrant itself and optimized its integration in widely used benchmarks like ann-benchmarks, demonstrating deep protocol-level knowledge. Based in Berlin, he wears multiple hats across product, infra, and client APIs while exploring frontend work in Vue.js. Colleagues know him for pragmatic engineering decisions that prioritize real-world performance and developer ergonomics.
12 years of coding experience
7 years of employment as a software developer
Bachelor's degree, Information technologies, with honor, Bachelor's degree, Information technologies, with honor at Bauman Moscow State Technical University
Русский, Английский
Stackoverflow
318reputation
13kreached
3answers
2questions
Github Skills (26)
back-end-development10
python10
qdrant10
nearest-neighbors10
vector-database10
database-design10
rest-api10
rust10
grpc10
api-design9
restful-api9
data-structure9
benchmark9
api-rest9
benchmarking9
Programming languages (15)
Github contributions (5)
qdrant/qdrant-client
Feb 2021 - Jan 2023
Python client for Qdrant vector search engine
Role in this project:
Back-end Developer
Back-end DeveloperContributions:20 releases, 225 reviews, 181 commits in 1 year 11 months
Contributions summary:Andrey primarily focused on enhancing the Qdrant client's functionality, as evidenced by the addition of parameters and methods. Their work included adding support for waiting parameters and integrating with Qdrant version 0.2.0 and 0.3.0. Furthermore, the user implemented methods for creating and deleting payload indexes, indicating an interest in optimizing payload handling. Also, the user implemented the feature for uploading data with gRPC and added the support for HTTPS.
vector-search-enginepythonpython-clientsearch-enginevector
qdrant/qdrant
May 2020 - Jan 2023
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Role in this project:Back-end Developer & Database Engineer
Back-end Developer & Database EngineerContributions:55 releases, 2320 reviews, 635 commits in 2 years 8 months
Contributions summary:Andrey primarily contributed to backend logic and database interactions within the Qdrant vector database project. Their commits involved significant changes to data structures and related database functions, particularly around how data is stored, indexed, and retrieved, as well as improvements for the efficient processing of internal data structures. Additionally, the user made changes in the API implementations, involving gRPC and REST, which indicates API-related development work.
pythonapproximate-nearest-neighbor-searchhnswsimilarity-searchvector
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