Software Engineering Manager, AI Platform
Software Engineering Manager, AI Platform
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
AI Platform Empowering X (APEX) team's mission is to accelerate and ensure the quality of the AI development lifecycle for Android and Pixel. In this role, you will build the stack for scaling the organization's machine learning (ML) needs, which include data strategies, model training, and evaluation techniques, incorporating human feedback for ML quality, on-device optimization, feature development, and quality experiments.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
Responsibilities include growing the local team experience and projects, mentoring team and removing bottlenecks; interfacing with cross-functional and remote teams, engineering managers, and stakeholders to influence cross-team priority and roadmap; designing tools/platforms/frameworks to enhance intelligent applications development, with focus on model evaluation, i18n, quality, and performance on Pixel and Android in a private and safe manner; crafting evaluation datasets, metrics, and pipelines to understand, evaluate and optimize the behavior of our models, platform and algorithms; and supporting a multitude of user-facing features that rely on the quality and performance of these algorithms, as running on compute-constrained embedded systems.