About the position
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. We're looking for a Principal Software Engineer to join the Elasticsearch - Search team. This globally-distributed team of expert engineers focuses on delivering a robust and feature-rich search experience, including contributing to improving the search experience in Lucene. This is a principal software engineering role that focuses on enhancing the vector similarity search functionality within Elasticsearch, covering the design and implementation of new vector search features, enhancements to existing vector search functionality, and resolving bugs.
Responsibilities
- Lead initiatives within Elasticsearch to produce an industry-leading vector database offering, supplying unparalleled speed and relevance in search.
- Contribute to Elasticsearch full time, building new search features and fixing intriguing bugs, all while making the code easier to understand.
- Invent new algorithms or data structures as needed.
- Work with a globally distributed team of experienced engineers focused on the vector search capabilities of Elasticsearch.
- Be an expert on how Elasticsearch implements vector similarity in support of search relevance.
- Work with community members from all over the world on issues and pull requests.
- Write idiomatic modern Java.
Requirements
- Implemented novel techniques in vector similarity on a search platform with a large user base or progressed the field of academic research in vector similarity information retrieval.
- Professional experience with vector similarity and vector databases, using HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale.
- Strong skills in core Java and familiarity with the standard library of data structures and concurrency constructs.
- Ability to work with a high level of autonomy, guiding projects from beginning to end.
- Comfortable developing collaboratively and giving/receiving feedback on code and approaches.
- Experience with several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra.
- Excellent verbal and written communication skills.
Nice-to-haves
- Experience building things with Elasticsearch.
- Familiarity with open source projects and different styles of source control workflow and continuous integration.
- Experience with data storage technology.
- Experience designing, leading and owning cross-functional initiatives.
Benefits
- Competitive pay based on the work you do here and not your previous salary.
- Health coverage for you and your family in many locations.
- Ability to craft your calendar with flexible locations and schedules for many roles.
- Generous number of vacation days each year.
- Financial donations and service matching up to $2000.
- Up to 40 hours each year to use toward volunteer projects.
- Minimum of 16 weeks of parental leave.
