Role focuses on enhancing Elasticsearch's vector similarity search (design, implement, and fix features), contributing to Lucene where relevant, working with a globally distributed engineering team, and writing idiomatic modern Java. Requires professional experience with vector similarity/vector databases (experience with HNSW, IVF, or similar), strong core Java skills, familiarity with data storage technologies, and experience collaborating on open source and distributed teams.

Join the globally distributed Elasticsearch Search team as a Principal Software Engineer to lead work on vector similarity search and vector database features (including algorithms like HNSW/IVF). Responsibilities include designing and implementing new vector search features, fixing bugs, improving relevance, collaborating with a distributed engineering and open source community, and writing idiomatic modern Java.

Lead design and implementation of vector search features and enhancements within Elasticsearch, contribute to Lucene improvements, triage and handle community issues, and write idiomatic modern Java. Requires professional experience with vector similarity algorithms (e.g., HNSW, IVF), distributed system development, and collaborative asynchronous communication.

Lead work on vector search within Elasticsearch: design and implement new vector search features, enhance existing vector similarity functionality (HNSW, IVF, etc.), fix bugs, and collaborate with a distributed team. Requires strong Java skills, experience with search platforms and vector databases, algorithm and data-structure expertise, and distributed-system experience.

Join Elastic's globally distributed Elasticsearch Search team as a Principal Software Engineer to lead development of vector similarity search features (including algorithms like HNSW/IVF), contribute to Lucene-related improvements, write modern Java, collaborate with open-source community members, and drive technical design and implementation for vector search capabilities.

Join the globally distributed Elasticsearch Search team to design and implement vector search features, improve vector similarity functionality, contribute to Lucene, and resolve related bugs. Role emphasizes idiomatic modern Java, algorithm and data-structure work, collaboration across a distributed team, and experience with vector databases and search platforms (HNSW, IVF).

Lead design and implementation of vector search features in Elasticsearch (including improving Lucene), work on vector similarity algorithms (HNSW, IVF, etc.), implement new algorithms or data structures, fix bugs, and collaborate with a globally distributed engineering and open source community. Requires strong Java skills, experience with vector databases and search at scale, distributed systems knowledge, and experience with related data storage technologies.

Join the Elasticsearch Search team as a Principal Software Engineer to design and implement vector search features, improve vector similarity functionality, and resolve related bugs. The role emphasizes building scalable, high-performance search capabilities (including work in Lucene), inventing or implementing algorithms/data structures, and collaborating with a globally distributed engineering and open-source community. Strong core Java skills and professional experience with vector similarity/vector databases (HNSW, IVF or similar) are required.

Join the globally distributed Elasticsearch Search team as a Principal Software Engineer to lead design and implementation of vector search features, improve vector similarity functionality (e.g., HNSW, IVF), fix bugs, and collaborate with a distributed open-source community. The role emphasizes strong Java, algorithms, data structures, concurrency, and distributed-systems skills and is based in/associated with Norway.

Join the Elasticsearch Search team to lead the design and implementation of vector search capabilities, improve relevance and performance, and contribute to Lucene improvements. The role requires expert-level Java, professional experience with vector similarity/vector databases (HNSW, IVF or similar), algorithm and data-structure work, and experience collaborating in distributed/open-source teams.

Principal Software Engineer role on the Elasticsearch Search team focused on designing and implementing vector similarity search features, improving existing vector search functionality, resolving bugs, and collaborating with a globally distributed engineering and open source community. The role emphasizes Java development, search algorithms (e.g., HNSW, IVF), data structures, concurrency, and performance at scale.

Lead development of vector search capabilities within Elasticsearch, designing and implementing new vector search features, improving existing functionality, fixing bugs, and collaborating with a globally distributed engineering and open-source community. Requires strong Java skills, experience with vector similarity techniques (e.g., HNSW, IVF) and working at scale with search or vector database systems.

Join Elasticsearch's globally distributed Search Relevance team to design and implement new search features, improve vector search capabilities (including HNSW/IVF and vector similarity), contribute to Lucene and Elasticsearch codebase, and collaborate with a distributed open-source community. The role emphasizes modern Java development, algorithm and data-structure work, and experience with search or vector databases.

Join the globally distributed Elasticsearch Search Relevance team as a Senior Software Engineer focused on vector search and search relevance. Responsibilities include designing and implementing new search features, improving relevance (including Lucene contributions), working with vector similarity algorithms (HNSW, IVF), and writing idiomatic modern Java in a distributed, open-source-oriented environment.

Senior Software Engineer role on the globally distributed Elasticsearch Search Relevance team. Responsibilities include designing and implementing search and vector-search features, improving search relevance (including work with Lucene), working with vector similarity algorithms (HNSW, IVF), contributing to open source, and collaborating asynchronously across a distributed team. Compensation range listed: €67,000–€106,000 EUR per year.

Join the globally distributed Elasticsearch Search Relevance team to design and implement vector search and relevance features, fix bugs, and improve search performance. Role emphasizes Java development, work with vector similarity algorithms (e.g., HNSW, IVF), collaboration on open source (GitHub), and contributions to Lucene/Elasticsearch. Location: Greece. Typical starting salary range indicated: €61,100–€96,600 EUR.

Join Elasticsearch's Search Relevance team to design and implement new search features, improve vector search capabilities (HNSW, IVF, vector similarity), work with Lucene, and write idiomatic modern Java on a globally distributed, open-source-focused team. Salary range provided in EUR.

Role involves designing and implementing new search features and enhancements in Elasticsearch (including contributions to Lucene), leading initiatives for vector search capabilities, working with algorithms like HNSW and IVF, collaborating with a globally distributed engineering and open-source community, and writing idiomatic modern Java.

Join the globally distributed Elasticsearch Search Relevance team to design and implement new search features, improve relevance, and fix issues in Elasticsearch/Lucene. The role emphasizes modern Java development, vector search algorithms (HNSW, IVF), working with large-scale search platforms and collaborating with a distributed open-source community.

Join the globally distributed Elasticsearch Search Relevance team to design and implement search features, improve vector search (HNSW, IVF and similar algorithms), contribute to Lucene and Elasticsearch codebase, write idiomatic modern Java, collaborate on open source issues and pull requests, and drive technical direction for search relevance.