Principal Software Engineer - Vector Search - Elasticsearch

Elastic, the Search AI Company, is looking for a Principal Software Engineer to join the Elasticsearch Search team, a globally distributed group of expert engineers who deliver the search experience in Elasticsearch and contribute upstream to Lucene. The role centers on the vector similarity search functionality within Elasticsearch: designing and implementing new vector search features, enhancing existing functionality, and resolving deep, intriguing bugs. Elastic is distributed by intention, collaborating across continents over email, GitHub, Zoom, and Slack, with every change code reviewed and big decisions made by consensus.

Responsibilities

• Lead initiatives within Elasticsearch to produce an industry-leading vector database offering with unparalleled speed and relevance in search.
• Contribute to Elasticsearch full time, building new search features and fixing bugs while making the code easier to understand, sometimes inventing a new algorithm or data structure, sometimes getting close to the operating system and hardware.
• Serve as the resident expert on how Elasticsearch implements vector similarity in support of search relevance, and improve the area based on your questions and instincts.
• Work with community members from around the world on issues and pull requests, triaging some and handling others yourself.
• Write idiomatic modern Java, Elasticsearch is 99.8% Java.

Qualifications

• You have implemented novel techniques in vector similarity on a search platform with a large user base, or advanced the field of academic research in vector similarity information retrieval.
• Professional experience with vector similarity and vector databases, including HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale.
• Strong skills in core Java: the standard library of data structures, concurrency constructs, and newer features like lambdas.
• High autonomy, able to take projects from technical design through delivery while coordinating with other engineers on needed components.
• Comfort with collaborative, asynchronous development over the internet, giving and receiving feedback on code, approaches, and APIs.
• Experience with several data storage technologies such as Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra, and an understanding of how and why they work.
• A proven track record of using AI to accelerate development, debug complex systems, and optimize code, while still owning the final outcomes.
• Bonus: prior work with Elasticsearch, open source contribution experience, and a history of designing and owning cross-functional initiatives.