Field Application Engineer, Cloud AI Infrastructure

engineeringjobs.net, Inc.; Town of Montana (WI); On-site; USD 159,000 - 230,000; Full time

Benefits offered by this job

Health benefits

401(k) with company match

PTO 20 days

Sick leave 40 hours/year

Maternity leave 28-30 weeks

Baby bonding leave 18 weeks

Holidays 13 paid days

Job summary

Google Cloud is seeking a Field Application Engineer (Hardware Engineer) to be an on-site, external-facing advisor for customers, driving hardware analysis, debugging, and issue resolution. You will conduct in-depth research into complex issues, troubleshoot across the platform, and provide expert solutions to help customers innovate with confidence.

You will partner with engineering and product teams to drive continuous improvement in Google Cloud hardware offerings and services, supporting

Qualifications

• Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience.
• 4 years of experience in debug or validation with CPU, dGPU, or TPU.
• 3 years of experience with technical infrastructure (deployment or maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
• 3 years of experience with hardware debug (e.g., silicon, platform, IO interface, or memory analysis).
• Experience with Linux/Unix systems and debugging issues across hardware/software boundary on enterprise-grade server infrastructure.
• Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, or virtualization).

Responsibilities

• Participate in on-call activities and manage server and data center CPU- and TPU-based activities, working with primary responders to resolve customer system observations.
• Manage customers' problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
• Work closely with Product, Quality, and Engineering teams to improve the product. Interact with our Site Reliability Engineering (SRE) teams to drive high-quality attainment.
• 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.

Skills

CPU/TPU debugging

System infrastructure

Hardware debugging

Linux/Unix debugging

Troubleshooting across stack

AI/ML hardware

Systems automation

Vendor/customer experience

Distributed systems

ML frameworks

Memory/IO tech

Education

Bachelor's degree in Computer Science or related field

Job description

Field Application Engineer, Cloud AI Infrastructure

Share

• Share Field Application Engineer, Cloud AI Infrastructure
• Copy link
• Email a friend

Location: Kirkland, WA, USA; Sunnyvale, CA, USA

Experience Level: Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Benefits

• 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

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Sunnyvale, CA, USA.

Minimum Qualifications

• Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience.
• 4 years of experience in debug or validation with CPU, dGPU, or TPU.
• 3 years of experience with technical infrastructure (deployment or maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
• 3 years of experience with hardware debug (e.g., silicon, platform, IO interface, or memory analysis).
• Experience with Linux/Unix systems and debugging issues across hardware/software boundary on enterprise-grade server infrastructure.
• Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, or virtualization).

Preferred Qualifications

• Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
• Experience with systems automation, and with systems design and debug.
• Experience working with vendors or customers.
• Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference lifecycle.
• Advanced understanding of memory and high-speed IO technologies.

About the Job

Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Field Application Engineer (Hardware Engineer), you will be an on-site, external-facing trusted advisor to customers, driving hardware analysis, debug, and issue resolution. You will do in-depth research into complex technical issues, troubleshoot critical issues across the platform, and provide expert solutions that help customers innovate with confidence. In this role, you will represent the customer, collaborating with engineering and product teams to drive continuous improvement in our products and services.

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 Salary Range

$159,000 - $230,000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Participate in on-call activities and manage server and data center CPU- and TPU-based activities, working with primary responders to resolve customer system observations.
• Manage customers' problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
• Work closely with Product, Quality, and Engineering teams to improve the product. Interact with our Site Reliability Engineering (SRE) teams to drive high-quality attainment.
• 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.

Privacy Policy

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit, is subject to Google's Applicant and Candidate Privacy Policy.

Equal Opportunity Employer

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.

See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Recruitment Agencies

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. based on an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.