Staff Software Engineer, Model as a Service, Cloud AI

Build infrastructure for model creators to be able to generate business with their models.Build a platform for partners to manage their services on Vertex.Work with sister teams to bring optimized models and serving techniques (e.g. prefix caching, cache-aware routing, etc.).Build infrastructure for efficiently onboarding open and closed source models to Google Cloud.Scale and maintain existing Model-as-a-service deployments.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 ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).Experience integrating generative AI tools or LLM interfaces into workflows.Experience with Kubernetes, C++, Go programming.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.5 years of experience with software development in Go, Python or Java programming languages.3 years of experience in a technical leadership role leading project teams and setting technical direction.3 years of experience with distributed system design of infrastructure software.Experience testing, maintaining, or launching software products, and with software design and architecture.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.The AI industry is rapidly adopting GenAI models due to their versatility and powerful capabilities in creating text, code, images, videos and more via increasingly more complex input context length. However, even the most technically competent businesses and GenAI developers will face challenges in development, scaling and managing the cost and infrastructure required to host such large models. Our Model as a Service (MaaS) aims to provide a much needed new level of abstraction to remove the complexity of development and provide large GenAI models as a scalable, cloud-based service with an enhanced suite of tools to facilitate the use, integration, and model management.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefitsLearn more about benefits at Google.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 ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).Experience integrating generative AI tools or LLM interfaces into workflows.Experience with Kubernetes, C++, Go programming.