Staff Systems Development Engineer, GCE Accelerators

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in systems administration.
• Experience using programming/scripting languages (such as PowerShell, Python, Bash, Go, etc).
• Experience in at least one of the areas of infrastructure (Linux, Kubernetes, Networking, Storage, etc.).
• Experience in network or Linux system administration, web or software development, and troubleshooting.

Preferred qualifications:

• 10 years of experience in systems administration.
• 4 years of experience in Computer Architecture performance analysis and optimization.
• Experience in open-source projects, particularly in AI/ML.
• Experience working with customers in a technical support or consulting role.
• Experience in the machine Learning system such as background theory, PyTorch/Tensorflow and other tools.
• Knowledge of automatic tools and frameworks deployed at scale within the machine learning fleet.

About the job

Systems Development Engineering (SDE) at Google is a role where you manage services and systems at scale. SDEs creatively put their engineering discipline to use automating the mundane and reducing toil. We don't just write code to fix bugs, but emphasize the development of tools and solutions that fix classes of problems. We know it's hard to control what you can't measure - so we focus on observability: instrumenting first, then turning data into knowledge, and finally knowledge into action. We know that the operational efficiency of Google systems, services, virtual compute environments and the operating systems that power them impact the environment, not just the bottom line. We know that working together we can do more, and that community matters.

Google brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow.

Together we engineer and build the infrastructure, tools, access and telemetry for systems that enable orchestration of Google-scale services. Come build things that matter.

The Google Compute Engine (GCE) AI Team's mission is to accelerate deployments and provide comprehensive support for large AI infrastructure customers throughout their entire life cycle. This includes assisting with pre-sales activities, proof-of-concepts, on boarding, production optimization, and migrations. By providing white-glove service and proactively addressing technical challenges, the team aims to ensure customer success and drive broader adoption of Google's AI infrastructure.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 $168,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Partner with customers to optimize the performance of AI/ML models on Google Cloud infrastructure.
• Dive deep into performance profiling, debugging, and troubleshooting of customer training and inference workloads.
• Collaborate with internal infrastructure teams to improve Google Cloud's ability to support demanding AI workloads.
• Develop and deliver high-quality training materials and demos to empower customers and internal teams.
• Contribute to the continuous improvement of our products by identifying and reporting bugs and suggesting enhancements.