Research Scientist focused on improving the computational efficiency of generative AI models (LLMs, Diffusion Models, Generative Videos) through foundational research in algorithmic efficiency, model compression, and inference acceleration. This role involves innovating algorithms, optimizing model architectures, improving the deployment pipeline (pretraining, tuning, RL), and collaborating with hardware/software teams to optimize inference engines and reduce latency/memory usage.

Research Software Engineer at Google Research focused on pioneering AI research in Singapore, specifically on developing performant, efficient, and capable generative AI models. The role involves abstracting problems, designing solutions, prototyping, profiling, benchmarking, and collaborating with global research and product teams.

Research Scientist role focused on Android security and AI agent safety, developing novel research and agent-powered systems to detect and prevent various forms of abuse. The role involves analyzing codebases using ML and collaborating with internal and external partners.

Research Scientist focused on protecting Android users from abusive apps by developing and publishing novel research on Android security and AI agent safety. The role involves designing neuro-symbolic and agent-powered systems, analyzing codebases using machine learning, and collaborating with internal and external partners to improve defenses against evolving threats.

Manager for a Data Science Research team focused on protecting Android users from AI-driven threats like malware and impersonation. The role involves leading technical strategy, identifying impactful data science problems, and driving the development of advanced quantitative methods, including ML modeling, to create data-driven products and solutions. This involves cross-functional collaboration with Engineering and Product leaders to translate research into business decisions.

This role focuses on applying advanced quantitative methods and machine learning to protect Android users from abusive applications. The data scientist will conduct end-to-end analysis, develop and evaluate ML models, and collaborate with product and engineering teams to improve safety systems. The work involves handling large datasets in an adversarial environment, aiming to detect and prevent various forms of abuse.