Applied Scientist – User Intelligence
Core
Develop and improve user personalization intelligence through architectural and data research to optimize targeting and pricing systems at planetary scale.
Role type
Senior Applied Scientist (User Intelligence & Personalization)
Builds
Real-time advertising targeting and pricing systems powered by attention-based architectures and multi-modal data
Domain
Digital Advertising / Machine Learning / E-commerce
Deliverable
production ML models
Required skills
Machine learning, deep learning, attention-based architectures, deep recommender systems, distributed data systems, PyTorch or JAX, model evaluation methodology, data pipeline construction
Preferred skills
Ads ecosystem knowledge (OpenRTB, SSPs, DSPs), peer-reviewed publications, industry track record at scale
Technologies
PyTorch, JAX, GPU compute platforms
Responsibilities
Build evidence-backed hypothesis pipelines and drive them to production, conduct architectural research for millisecond-level latency, advance offline and online evaluation methodologies, leverage product data features to improve models, contribute to internal model implementations and training pipelines, guide infrastructure teams on experimentation velocity, maintain an active external research profile
Seniority
Senior, hands-on IC with research leadership
