The User Signal team sits at the heart of our in-house advertising platform. We collect, process, and activate user signals — behavioral events, contextual data, engagement history, and identity signals — and turn them into the features and audiences that power ads targeting, bidding, and ranking across the company’s ad stack.
The quality of our signals directly determines how well every downstream ML model performs: better signals mean better targeting, higher CTR/CVR, and stronger monetization. We own the full lifecycle — from raw event ingestion and large-scale feature pipelines, to identity-prediction models, embeddings, and online serving — and we close the loop by applying those outputs inside the ads models that consume them in real time.
We are looking for an experienced Senior Machine Learning Engineer to design and build the data and ML systems that transform raw user signals into production targeting and bidding features. This is a hands-on, high-ownership role that blends ML modeling, large-scale data engineering, and production ML systems.
You will own significant pieces of the signal-to-model pipeline end to end: defining and building features at scale, developing models for user understanding — most importantly identity prediction — and then applying those predictions directly inside the ads targeting, bidding, and ranking models to drive measurable lift. You won’t just hand features off to a downstream team; you’ll close the loop, ensuring everything is served online with the freshness, latency, and reliability that real-time bidding demands. You’ll partner closely with Ads, Data, and Infra teams, and you’ll be expected to drive technical direction — not just execute well-scoped tasks.