Senior Software Engineer, Backend and AI Systems, Flow
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Minimum qualifications:
- Bachelor’s degree in Computer Science or related technical field, or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., Java, C++, Python, Kotlin, or Go).
- 3 years of experience testing, maintaining, or launching scalable software products, 1 year of experience with backend software design and distributed system architecture.
- 3 years of experience with one or more of the following: Generative AI, computer vision, media processing, ML infrastructure, or backend systems for AI products.
- 3 years of experience with ML infrastructure (e.g., model deployment, inference, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 5 years of experience with data structures, algorithms, and software design optimization.
- 1 year of experience in a technical leadership role, driving technical direction in 0-to-1 project environments or startups.
- Experience with Google-specific technologies (e.g., Boq, Spanner) or building backend systems for generative AI (e.g., LLMs, diffusion models) and enterprise-grade applications.
- Experience developing accessible technologies or user-centric tools for creative expression.
About the job
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 manage information at a 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 changing 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.Google Flow is an exciting new product from Google Labs that empowers creators to generate high-quality video and image content for professional and entertainment use cases. Born from the same team that launched ground-breaking technologies like MusicLM, Veo, and ImageFx, Flow is building on this momentum to expand significantly.
We are moving from an early-adopter focus to a massive scale, targeting both mobile experiences and enterprise-grade reliability. This is a rare opportunity to work in a "0-to-1" environment within Google, building the backbone of a product that sits at the nexus of Generative AI models and user-centric product needs.Labs is a group focused on incubating early-stage efforts in support of Google’s mission to organize the world’s information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer timeframes.
Responsibilities
- Write and test scalable backend product or system development code to support high-volume AI media generation, storage, and retrieval.
- Collaborate with research scientists, designers, and cross-functional stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., model hosting, versioning, inference systems, and API efficiency).
- Design and implement solutions in specialized ML infrastructure areas, leveraging backend expertise to build robust pipelines for generative media models (e.g., video/image generation), and demonstrate expertise in distributed systems.
- Triage backend system issues and debug/track/resolve by analyzing the sources of issues and the impact on model inference, storage, network operations, and service quality.
- Contribute to existing documentation or educational content regarding system architecture and API specifications, and adapt content based on GenAI model updates and user feedback.
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