Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a technical role where you will be responsible for the success of complex Search Query feature development.
This role is based in our San Francisco office.
You would get to:- Lead complex projects across the MongoDB ecosystem, for instance, co-optimization of approximate nearest neighbor vector search with the MongoDB aggregation framework
- Set project level strategy, architect features, and lead projects to successful execution
- Identify, design, and implement features enhancing our query language, performance, and operability
- Perform code reviews with peers and make recommendations on how to improve our software development processes
- Influence and grow team members through active mentoring and leading by example
Ideally, you will be:- 5+ years experience in data management systems, ideally with a strong query processing and optimization background
- Experienced in developing stateful distributed systems
- Experienced with designing high-volume query engines, such as a database, search system, or vector search system
- Experienced in the development and maintenance of stateful distributed systems
- Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others
- Experienced in debugging and profiling multithreaded JVM applications
Success Measures:- In 1 month, you will be mostly learning - becoming familiar with our teams, systems and architecture
- In 3 months, you'll contribute to the improvement of our search engine service
- In 6 months, you'll be designing new features and collaborating with other teams from across the company on projects related to search query optimization and execution