Staff Software Engineer, ML Supercomputer Reliability

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.
• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
• 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/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.
• Knowledge of common ML algorithms and how they map to software and hardware operations.
• Knowledge of networking, especially at the link layer, along with routing algorithms and topologies.

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.

The ML Supercomputers team is at the forefront of powering Google's accelerator products. They drive the research, design, and development of core systems software and networking technologies for these platforms. Their primary focus is solving the critical issue of scaling Machine Learning (ML) workloads to counteract the limitations of Moore's Law.

The mission is to deliver easy-to-use and maintainable software for the reliable scale-out and scale-up of accelerators, specifically targeting massive-scale ML applications. In this role, you will be working on complex problems, such as building scalable software to detect and manage faults in massive-scale all-gather operations.

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.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Design and maintain supercomputer software across different layers of the software stack (e.g., network routing rules built into Tensor Processing Units (TPUs), control software running on specialized machines, distributed software running on Google’s internal and cloud infrastructure).
• Control, monitor, build, deploy, qualify, and service supercomputing systems.
• Provide technical leadership to help formulate and drive software development plans.
• Identify commonalities between different supercomputer generations and accelerator types and create well abstracted and flexible software.
• Help identify dependencies in cross-functional teams and drive common execution with a focus on development velocity and quality.