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Senior Backend Engineer, Care Platform & EMR
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…maintaining high standards for reliability, testing, and software…
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Remote, United States
…maintaining high standards for reliability, testing, and software…
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Google

Customer Solutions Engineer, Compute, Google Cloud

Kirkland, WA, United States

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Job details

Posting language: English

Original job description

In most instances, this position requires in-person interviews as part of the hiring process.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees.

Benefits for this role include:

Health, dental, vision, life, disability insurance
Retirement Benefits: 401(k) with company match
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
Baby Bonding Leave: 18 weeks
Holidays: 13 paid days per year

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.
Experience with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.

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. This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.

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.

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.

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More about this job

Skills

Google Cloud
Debugging
Oracle Java
C
C++
Python
Go
JavaScript
Troubleshooting
Firmware
Linux
UNIX
ML
TensorFlow
PyTorch
Kubernetes
Troubleshoot
System administration
Documentation
Hardware architectures
Sales

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Jobs in the United States