Customer Solutions Engineer, Compute, Google Cloud

MINIMUM QUALIFICATIONS:

* Bachelor's degree in Science, Technology, Engineering, Mathematics, or

equivalent practical experience.

* Experience in reading/debugging code written in a general purpose coding

language (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.) and in

virtualization and orchestration frameworks.

* Experience troubleshooting and advocating for customer needs, and triaging

technical issues across the stack (e.g., hardware faults, low-level software,

networking, virtualization, kernel drivers, firmware, performance).

* System administrator level experience with Linux/Unix systems and experience

in debugging issues across the hardware/software boundary on enterprise-grade

server infrastructure.

PREFERRED QUALIFICATIONS:

* Experience working with large-scale distributed systems, and familiarity with

common solutions, design patterns, or best practices.

* Experience working directly with AI/ML computing hardware, including GPUs or

other accelerators.

* Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding

of the AI/ML training and inference lifecycle.

* Familiarity with containerization and orchestration technologies like

Kubernetes or Slurm in an on-prem or cloud environment.

ABOUT THE JOB:

Our Solutions Engineers for AI Infrastructure own complex customer issues and

provide specialized support to other teams.

In this role, you will

• be a part of
• a global team that provides 24x7 support to ensure customers can seamlessly
• deploy their AI and ML workloads on AI Infrastructure products. When customers
• encounter deep technical issues, your job is to ensure we have the expertise,
• tools, and processes to resolve the issue. You will troubleshoot technical
• problems with a mix of hardware and software debugging, networking, Linux system
• administration, coding/scripting, and updating documentation. You will help our
• customer’s success in the AI/ML space by making improvements to the product,
• internal tools, processes, and documentation. You'll help drive business growth
• by recognizing and advocating for our customers’ challenges related to AI
• deployments.
• 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.
• Individual pay is determined by factors including job-related skills,
• experience, and relevant education or training.
• US: $102000 - $144000 (USD) + 15% bonus target + equity + benefits
• Learn more about benefits at Google
• [https://www.google.com/about/careers/applications/benefits/].
• RESPONSIBILITIES:
• * Manage customers' problems through effective diagnosis, resolution, or
• implementation of new investigation tools to increase productivity for
• customer issues on AI/ML infrastructure.
• * Develop an in-depth understanding of AI/ML workloads and underlying hardware
• architectures by troubleshooting, reproducing, determining the root cause for
• customer reported issues, and building tools for faster diagnosis.
• * Act as a consultant and subject matter expert for internal stakeholders in
• Engineering, Sales, and customer organizations to resolve complex deployment
• and operational obstacles in AI infrastructure environments.
• * Work closely with multiple Product and Engineering teams to find ways to
• improve the product, and interact with our Site Reliability Engineering (SRE)
• teams to drive high-quality production.
• * Be available for non-standard work hours or shifts which may include weekends
• as needed.