Senior Software Engineer - Vector Search - Elasticsearch

Elastic; Polska; Presencial; PLN 180.000 - 300.000; Jornada completa

Descripción de la vacante

Elastic, the Search AI Company, is seeking a Senior Software Engineer to join the Elasticsearch - Search Relevance team. You will lead initiatives to deliver an industry-leading search engine, focusing on speed and relevance across a globally distributed platform.

This role requires deep Java expertise, experience with vector search, and a drive to own end-to-end solutions within a collaborative, asynchronous-friendly environment. Join a team that values open collaboration across continents.

Formación

• Proven experience with search or vector databases at scale.
• Knowledge of HNSW and IVF algorithms is a plus.
• Strong Java core skills and concurrency understanding.

Responsabilidades

• Lead initiatives within Elasticsearch to deliver fast, relevant search.
• Design and implement new search features and fix complex bugs.
• Collaborate with a globally distributed team on vector search capabilities.
• Triage issues, review PRs, and drive architectural decisions.

Conocimientos

Java

Vector similarity

Search relevance

Herramientas

Elasticsearch

Solr

PostgreSQL

MongoDB

Cassandra

Descripción del empleo

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. What is The Role We're looking for a Senior Software Engineer to join the Elasticsearch - Search Relevance 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 technical leader is responsible for contributing to the technical direction and vision for our search capabilities, including design and implementation of new search features, enhancements to search functionality, and resolving bugs. Our company is distributed by intention. We hire the best engineers we can find wherever they are, whoever they are. We collaborate across continents every day over email, GitHub, Zoom, and Slack. At our best, we write fast, scalable and intuitive software. We believe that the best way to do that is to empower individual engineers, code review every change, decide big things by consensus, and strive for incremental improvements.

What You Will Be Doing

Lead initiatives within Elasticsearch to produce an industry-leading search engine 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. 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. Work with a globally distributed team of experienced engineers focused on the vector search capabilities of Elasticsearch. Be an expert on Elasticsearch search relevance. You'll identify and drive improvements this area based on your questions and your instincts. 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. Write idiomatic modern Java -- Elasticsearch is 99.8% Java!

What You Bring

You have 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 search or vector databases, and you used HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale. You have solid skills in core Java and are conversant in the standard library of data structures and concurrency constructs, as well as other features like lambdas. You work with a high level of autonomy and are able to take on projects and guide them from beginning to end. This covers both technical design and working with other engineers to develop needed components. You're comfortable developing collaboratively. Giving and receiving feedback on code and approaches and APIs is hard! Bonus points if you've collaborated over the internet because that's harder. Double bonus points for asynchronous collaboration over the internet. That's even harder, but we do it anyway because it's the best way we know how to build software. You've used several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra and have some idea how they work and why they work that way. You have a proven track record of using AI to accelerate development, debug complex systems, and optimize code, while still owning the final outcomes. You possess the ability to collaborate across functions and teams and seamlessly transition between different projects, codebases, or teams based on business priorities You work autonomously and can drive decisions and results in a distributed team by leveraging asynchronous, direct, and transparent communication.

Bonus Points

Bonus Points You've built things with Elasticsearch before. You've worked with open source projects and are familiar with different styles of source control workflow and continuous integration. Experience with data storage technology. You have experience designing, leading, and owning cross-functional initiatives.

Compensation for this role is in the form of base salary. This role does not have a variable compensation component. At Elastic, our compensation philosophy aims to provide fair, competitive and transparent remuneration. Salary ranges are established based on a combination of external market benchmarks, internal pay equity considerations, and the.