Lead data science for consumer monetization across subscriptions, advertising, and virtual currencies, defining success metrics and experiments and translating behavioral and economic data into product decisions.
Lead end-to-end AI infrastructure programs across training, evaluation, and inference, aligning engineering, research, and product teams on roadmaps, execution, reliability, and scalable systems.
Design and scale backend systems and applied machine learning solutions that detect, prevent, and mitigate integrity risks, strengthening safety across human-to-AI interactions.
Build and optimize applied ML models, infrastructure, and backend systems for discovery, recommendation, ranking, and search, spanning data pipelines, model training, and production serving.
Build and maintain scalable backend services and secure APIs, improving performance, reliability, and availability while collaborating with product, data, and frontend teams.
Build and improve mobile and web monetization features spanning payments, subscriptions, virtual currency, and in-app purchases, creating trustworthy user experiences and driving measurable engagement and revenue outcomes.
Build polished, high-performance interfaces for consumer products, shaping user experiences and product features while establishing consistent design systems in close collaboration with design and engineering teams.
Develop and evaluate safety and alignment methods for large language models, uncover vulnerabilities through adversarial testing, and translate research into scalable product solutions.
Design and maintain machine learning training and serving infrastructure, helping research and product teams diagnose cluster issues, manage experiments, monitor deployments, and maximize GPU utilization.
Develop post-training methods for language models, improving alignment, data efficiency, real-world quality, and serving performance to shape conversational experiences for millions of users.
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