Senior Staff Software Engineer, AI/ML, Google Cloud

Google•Seattle, WA

4d•$262,000 - $364,000

About The Position

Google software engineers develop technologies that enable users to connect, explore, and interact with information at massive scale. Engineers work on projects critical to Google, with opportunities to move across teams and projects, and are expected to demonstrate versatility, leadership, and enthusiasm for solving problems across the full stack. The Cloud GPU team builds and maintains Google Cloud’s GPU fleet and AI Platform, providing computational resources for sophisticated training and inference workloads. The team manages the lifecycle of GPU offerings, from launching new GPU families to ensuring reliability and operational excellence. Working across hardware, software, data science, and applied AI, the team collaborates with internal and external partners to deliver infrastructure for AI advances. The AI and Infrastructure team delivers AI and infrastructure at scale, efficiency, reliability, and velocity for Google users and customers. Its work includes developing AI models, providing computing power for global services, and building platforms for developers, including TPUs, Vertex AI, global networking, data center operations, and systems research. Individual pay is determined by job-related skills, experience, and relevant education or training. The US salary range is $262,000–$364,000, plus a 25% bonus target, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure, such as model deployment, model evaluation, data processing, debugging, and fine-tuning.
5 years of experience with design and architecture, and testing and launching software products.

Nice To Haves

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 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.

Responsibilities

Execute technical roadmaps for the GPU ecosystem, anticipating market shifts to keep Google Cloud at the forefront of AI infrastructure.
Collaborate with engineering teams to integrate new GPU architectures into Google Compute Engine (GCE) for rapid workload availability.
Oversee the lifecycle of accelerator solutions, ensuring consistent performance and stability for user applications.
Serve as a technical advocate during critical issues, collaborating directly with customers to resolve challenges and translating their feedback into platform enhancements.
Design robust software solutions that meet the massive scalability and performance requirements of Google Cloud’s global network.