Senior Software Engineer - Search Relevance in Es|ql - Elasticsearch

Elastic Elastic · Enterprise · United States · Platform - Elasticsearch

Senior Software Engineer role focused on Search Relevance within Elasticsearch, contributing to the core search engine, vector search capabilities, and leveraging AI for development acceleration. The role involves leading initiatives, designing and implementing new search features, and working with a globally distributed team.

What you'd actually do

  1. Lead initiatives within Elasticsearch to produce an industry-leading search engine offering, supplying unparalleled speed and relevance in search.
  2. Contribute to Elasticsearch full time, building new search features and fixing intriguing bugs, all while making the code easier to understand. Sometimes you'll need to invent a new algorithm or data structure. Or find one and implement it. Sometimes you'll need to get close to the operating system and hardware.
  3. Work with a globally distributed team of experienced engineers focused on the vector search capabilities of Elasticsearch.
  4. Be an expert on Elasticsearch search relevance. You'll identify and drive improvements this area based on your questions and your instincts.
  5. Work with community members from all over the world on issues and pull requests, sometimes triaging them and handing them off to other experts and sometimes handling them yourself.

Skills

Required

  • Search relevance
  • Vector databases
  • HNSW
  • IVF
  • Java
  • Data structures
  • Concurrency constructs
  • Autonomy
  • Technical design
  • Collaboration
  • Data storage technologies
  • AI for development acceleration
  • Cross-functional collaboration
  • Asynchronous communication

Nice to have

  • Elasticsearch experience
  • Open source contribution
  • Source control workflow
  • Continuous integration
  • Data storage technology experience
  • Designing, leading, and owning cross-functional initiatives

What the JD emphasized

  • vector search capabilities
  • vector databases
  • search platforms at scale
  • core Java
  • standard library of data structures and concurrency constructs
  • high level of autonomy
  • technical design
  • working with other engineers
  • collaboratively
  • Giving and receiving feedback on code and approaches and APIs
  • data storage technologies
  • Elasticsearch
  • Solr
  • PostgreSQL
  • MongoDB
  • Cassandra
  • using AI to accelerate development
  • debug complex systems
  • optimize code
  • owning the final outcomes
  • collaborate across functions and teams
  • seamlessly transition between different projects, codebases, or teams
  • business priorities
  • work autonomously
  • drive decisions and results
  • distributed team
  • asynchronous, direct, and transparent communication

Other signals

  • Elasticsearch
  • Search Relevance
  • Vector Search
  • AI