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 Kubernetes Engine (GKE) is the industry standard for container orchestration and the core of Google Cloud’s modernization strategy. We are now embarking on a mission to reinvent GKE and Kubernetes as the premier substrate for the next generation of AI-ML workloads. The GKE AI Data organization is a critical, high-growth technical domain core to GKE’s business. The team is deeply involved in building storage solutions and data pipelines for the AI-ML workloads including training, inference, RL and agentic workflows.
In this role, you will solve complex storage problems through solutions working at the intersection of K8s (kubernetes), AI-ML and Storage. You will drive the agenda in close collaboration with leads across other storage organizations inside Google and in Open Source.
The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Guide the architectural direction for GKE AI Data ensuring a scalable, performant and efficient storage solution for AI-ML workloads running on K8s across block, file and object storage.
- Drive storage solutions for evolving AI/ML issues, including KV Caching, fast model loading, and re-envisioning storage for agentic workloads (e.g., fast suspend/resume and shared multi-agent storage).
- Partner with multiple storage teams in google cloud platform (GCP) to drive alignment and clarity around strategy and execution.
- Lead the broader Kubernetes ecosystem and Open Source Software (OSS) community, driving key upstream initiatives to establish industry standards for storage solutions.
- Imagine, architect, and lead the technical execution of industry-defining standards through both direct, technical work and by mentoring and guiding teams of engineers.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience programming in C++.
- 5 years of experience with design and architecture; and testing/launching software products.
Preferred qualifications:
- Deep expertise in AI/ML infrastructure, specifically regarding storage and caching solutions.
- Demonstrated track record of significant technical contributions to the Kubernetes open-source project or related CNCF or PyTorch AI/ML projects.
- Demonstrated track record of influencing cross-functional teams (Product, Engineering, Research) to deliver complex technical outcomes.