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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 contribute to improvements in Lucene. This technical leader will drive the vision for search capabilities by designing and implementing new features, resolving bugs, and developing novel algorithms or data structures. The role involves building vector search capabilities within Elasticsearch while collaborating with a globally distributed team of engineers. Key responsibilities include triaging community pull requests and writing idiomatic modern Java code. Candidates must possess expertise in vector similarity, including HNSW and IVF algorithms, alongside proficiency in core Java, concurrency constructs, and various data storage technologies like Solr, PostgreSQL, MongoDB, or Cassandra. The position focuses on solving complex search relevance problems by providing high-speed results for both structured and unstructured data within the Elasticsearch platform.
What does a Software Engineer earn in Remote?
Median $204500 from 415 postings across 57 companies.
Design and implement new search features and enhancements to improve search functionality and relevance.
Develop, optimize, and maintain the Elasticsearch core codebase using modern Java.
Create new algorithms or data structures to improve search performance and speed.
Identify and drive technical improvements for vector search capabilities within the platform.
Resolve complex bugs and refactor code to improve maintainability and readability.
Manage community interactions by triaging and resolving issues and pull requests from global users.
Lead technical initiatives and provide direction for the search capabilities roadmap.
Ensure all software contributions comply with security standards and data protection policies.
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 HNSW, IVF, or other relevant algorithms and libraries at scale.
Proficiency in core Java, including the standard library of data structures, concurrency constructs, and lambdas.
Ability to work autonomously to lead projects from technical design through implementation in a distributed team environment.
Experience with various data storage technologies such as Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra.
Proven track record of using AI to accelerate development, debug complex systems, and optimize code.
Familiarity with open source projects, source control workflows, and continuous integration.