This role is based in the SF Bay Area - hybrid work model.
You would get to:
Design and contribute to our integrated search platform to support ML workloads.
Participate in product and architecture discussions
Perform code reviews with peers and make recommendations on how to improve our code and software development processes
Collaborate with other teams including cloud services, database, enterprise tools, drivers and support to coordinate changes or contribute to their projects
Ideally you will be:
3+ years experience delivering large scale systems on production.
Proficient in modern programming languages and techniques preferably Java and Python.
Experienced in developing distributed systems, cloud services and SaaS products
Experience with building Gen AI applications or tools like langchain, llama index is preferred but not required.
Success Measures:
In three months, you will contribute to search repos to build the foundation for embedding management in MongoDB as well as develop relationships with your team and leaders on other teams.
In six months, you will have delivered a key feature and contribute to new ML capabilities in Atlas Search.
In twelve months, you'll be building POCs, designing new features, and collaborating with other Cloud and Server teams on complex projects.