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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
YouTube Create is a dedicated, Artificial Intelligence (AI)-powered video editing app designed to help engaged and purposeful creators in creating, editing, enhancing and crafting their videos for publishing on YT and beyond. The app is a leading effort to bring more powerful and helpful creation tools to people, on their mobile devices, utilizing Google’s deep Machine Learning (ML) and Generative AI expertise to make the process of creating and editing videos easier and faster.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.
Responsibilities
- Provide technical leadership on high-impact projects. Guide the adoption of technologies, including Generative AI, AI Editing agentic framework and on-device, real-time models across vision, audio, and language modalities.
- Influence and coach a distributed team of engineers.
- Facilitate alignment and clarity across teams to define product strategy, influence feature roadmaps, and drive the rapid prototyping and delivery of completely new creator workflows.
- Manage project priorities, deadlines, and deliverables. Direct the technical collaboration with the Advanced Capabilities team, seamlessly bridging the gap between highly specialized research, rapid prototyping, and robust production infrastructure.
- Design, develop, test, deploy, maintain, and enhance large scale software solutions.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with computer vision (e.g., image classification and processing, object detection, visual search), video generation, or signal processing; and experience with various algorithms and design techniques.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with training, optimizing and productionizing ML models.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience with the entire ML stack: data preparation, training, evaluation, and performance benchmarking.