Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
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.
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 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.
Google Cloud Storage’s mission is to provide the most trusted planet-scale storage system, with reliability, efficiency, performance, and simplicity.
The Storage AI/ML Solutions team is dedicated to exploring, architecting and developing next-generation storage solutions for the AI/ML ecosystem. We bridge the gap between core storage infrastructure and the evolving demands of AI/ML workloads, from large-scale training to high-performance inference. By delivering innovative solutions and sharing performance insights through benchmarks, we enable customers to achieve optimal results and solidify Google Cloud Platform (GCP's) position as the premier platform for AI/ML.
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.
Responsibilities
- Design and implementation of high-complexity features. Deliver production-ready code for storage solutions that address the specific demands of AI/ML workloads.
- Architect scalable and performant storage solutions. Make data-driven decisions to optimize system efficiency and reliability.
- Identify and resolve performance bottlenecks and intricate system issues. Develop innovative, practical solutions to technical issues that arise at the intersection of storage and ML.
- Partner with product and engineering stakeholders to translate customer requirements into technical specifications, ensuring the incubation’s output aligns with broader Google Cloud goals.
