Job Description

We're Meta's Standalone Apps Team — we build new apps to reach new user scenarios and serve needs that aren't well met today. The project we're building right now is an image-and-text community where real people share first-hand experiences and recommendations — what to try, where to go, how to do something. It's where people come to get inspired and to make everyday decisions, learning from others who've actually been there. It's still early — a small team working 0→1.

If you want high ownership, a short path from idea to ship, and the chance to shape a product from its first version, this is that kind of team.

We're looking for a staff-level ML engineer to own the search algorithm — retrieval, ranking, and relevance — so people can find exactly what they're looking for.

Responsibilities
Own the modeling and systems direction for search — retrieval, ranking, query understanding, and relevance.
* Define search-quality metrics and the experimentation approach; drive measurable relevance gains.
* Build and scale the ML and serving systems search depends on.
* Set technical direction across teams; align search work with product strategy.
* Mentor ML and product engineers; raise the bar on modeling and evaluation rigor.

Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
* 12+ years of relevant experience, with deep expertise in search / information retrieval / ranking
* Strong foundation in ML and in the systems that train and serve models at scale
* Track record of driving search/relevance improvements that moved product metrics
* Experience setting technical direction across multiple teams Experience building search for a new product (0→1)
* Experience with semantic/embedding retrieval, query understanding, or large-scale search infrastructure
* Publications or recognized contributions in IR/search/ML