Senior Platform Application Engineer, Cloud AI Infrastructure

Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. 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. You will dive deep into complex technical challenges, troubleshoot critical issues across the platform, and provide resolutions in both short-term and long-term platform solutions. In this role, you will represent the customer solution, collaborating tightly 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: $188000 - $274000 (USD) + 20% bonus target + equity + benefits, * 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 behaviors.
• 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.

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * Bachelor’s degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.

• 6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
• 6 years of debug or validation experience with CPU, dGPU, or TPU
• 5 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
• Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
• Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure., * 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 systems automation, and with systems design and debug.
• 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.
• Understanding of memory and high-speed IO technologies.

XIn 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 (statutory, where applicable); 5 days/event (discretionary)
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year.

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 alsoGoogle’s EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC_KnowYourRights_10_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

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.

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.