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.
Responsibilities
Participate in on-call activities and manage the systems within the domain and work with the primary responders to help in fixing system issues
Troubleshoot technical issues, evaluate technical data, and develop recommendations for systems and services, respond to tickets/bugs within team-defined service-level objectives (SLOs), and contribute to systems and services through bug reports and consultation
Work with customers on defining distributed systems requirements, testing procedures, and proposing solutions
Set up processes for planning, improving quality, best practices, and maintaining a short response time for user issues
Requirements
Bachelor's degree in Computer Science, or a related Information Technology (IT) field, or equivalent practical experience
Nice to have: Electronic Design Automation (EDA) tools
As a Platform Application Engineer (Hardware Engineer), you will be focused on solving customer observations by, driving deep hardware analysis, debug, and issue resolution through to the root cause.
Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
Work closely with multiple Product, Quality, and Engineering teams to improve the product, and interact with our Site Reliability Engineering (SRE) teams to understand behaviours.
Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
Requirements
Bachelor's degree in Computer Science
Bachelor's degree in Management Information Systems