Elastic is looking to enhance its vector search functionality within the Elasticsearch platform to provide an industry-leading vector database offering with unparalleled speed and relevance in search.
Requirements
- 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.
- You've made broad industry-wide contributions to search relevance or related topics in information retrieval.
- Professional experience with vector similarity and vector databases, and you used HNSW, IVF, or other relevant algorithms and libraries on search platforms at scale.
- You have strong 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'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'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.
Responsibilities
- Lead cross organizational initiatives 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.
- 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 how Elasticsearch implements vector similarity in support of search relevance and everyone will turn to you when they have a question about this area.
- 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.
Other
- This is a senior principal software engineering role that focuses on enhancing the vector similarity search functionality within Elasticsearch, defining and implementing a future-facing roadmap for vector search within Elasticsearch, covering the design and implementation of new vector search features, enhancements to existing vector search functionality, and resolving bugs.
- 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!
- You have excellent verbal and written communication skills.
- You have experience designing, leading and owning cross-functional initiatives
