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$165,650–$212,950.
Based on 240 similar postings.
Employer
About Elastic
Elastic is the company behind Elasticsearch and the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash). It sells search, observability, and security products built on that search engine, primarily through its Elastic Cloud managed service.
Elastic currently has
240 open roles
on FindRole.
Listed pay typically runs
$133,100–$210,600
across 91 roles with salary data.
Senior Software Engineer - Vector Search - Elasticsearch joins the Search Relevance team to deliver a robust, feature-rich search experience and improve Lucene capabilities. This technical leader will drive the vision for search features, design and implement new functionalities, resolve bugs, and develop novel algorithms or data structures while ensuring code remains maintainable. The role focuses on vector search capabilities within the Elasticsearch platform. Key responsibilities include collaborating with a globally distributed team, engaging with community members on pull requests, and optimizing search relevance. Candidates must possess expertise in core Java, including standard libraries, concurrency constructs, and lambdas. Required skills include experience with vector similarity techniques like HNSW or IVF, as well as familiarity with data storage technologies such as Solr, PostgreSQL, MongoDB, or Cassandra to solve complex information retrieval problems at scale.
What does a Software Engineer earn in Remote?
Median $204500 from 415 postings across 57 companies.
Lead initiatives to develop an industry-leading search engine with high speed and relevance.
Design and implement new search features, improvements to functionality, and complex bug fixes.
Develop novel algorithms or data structures for vector similarity and information retrieval.
Write idiomatic, modern Java code while maintaining and improving the existing codebase.
Act as a subject matter expert to identify and drive improvements in search relevance.
Manage community interactions by triaging and resolving issues and pull requests from global users.
Drive technical projects from inception to completion, including design and cross-functional coordination.
What we're looking for
Experience implementing novel techniques in vector similarity on a search platform or advancing academic research in vector similarity information retrieval.
Professional experience with search or vector databases using algorithms like HNSW and IVF at scale.
Proficiency in writing idiomatic modern Java, including the standard library of data structures and concurrency constructs.
Ability to work autonomously to lead projects from initial technical design through completion.
Proven track record of using AI to accelerate development, debug complex systems, and optimize code.
Experience with various data storage technologies such as Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra.
Ability to collaborate effectively in a distributed team environment using asynchronous communication.