Cloud Engineer Jobs in Austin, TX

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

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

Minimum qualifications:

• Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience.
• 8 years of experience with Linux/Unix systems and experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
• 5 years of experience in technical leadership.
  
• 3 years of experience with technical infrastructure (e.g., deployment, maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
• 3 years of debug or validation experience with CPU, dGPU, or TPU.
• Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).

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

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.