Staff Applied Scientist- Recommendation Systems
Core
Design, build, and deploy large-scale recommendation and personalization models to power discovery and shopping experiences across Glance's consumer technology platforms.
Role type
Staff Applied Scientist (Recommendation Systems)
Builds
Personalization models and ML pipelines for mobile lock screens, live video platforms, and gaming apps.
Domain
Consumer Technology / E-commerce / Mobile Apps
Deliverable
production ML models
Required skills
Machine Learning, Deep Learning, NLP, Reinforcement Learning, Time Series, Statistics, Python, Apache Spark, Cloud Platforms (AWS/GCP/Azure), A/B Testing, Causal Reasoning
Preferred skills
Identity-constrained/privacy-aware environment experience, PhD
Technologies
Python, Apache Spark, Vertex AI, GCP, AWS, Azure
Responsibilities
Design and deploy large-scale recommendation models; lead rapid experimentation from hypothesis to online A/B testing; develop end-to-end ML pipelines; partner with Product and Engineering to translate goals into ML solutions; monitor model health and performance; prototype new ML techniques for relevance and engagement.
Seniority
Staff, hands-on IC with strategic impact
