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Supportability Technical Lead, AI/ML, Google Cloud

Google3,326 open roles

Where
Austin, TX, USA; Sunnyvale, CA, USA
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Your applicationOpen nowSupportability Technical Lead, AI/ML, Google CloudGoogle · Austin, TX, USA; Sunnyvale, CA, USA
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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.4%3 days
  3. 7.9%7 days
  4. 14.2%14 days
  5. 34.1%30 days
This job: first seen 5 hours ago

Google median: 26 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Sunnyvale, CA, USA.

Minimum qualifications:

  • Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  • 9 years of experience in a technical role (e.g., Technical Solutions Engineer, Software Engineer, Customer Engineer, Professional Services, or Technical Program Management), troubleshooting or triaging technical issues.
  • Experience in Google Cloud Platform, ADK, Generative AI and with AI model training, testing, evaluation, and tuning processes.
  • Experience with web technologies (e.g., HTTP, HTML, DNS, TCP).
  • Experience leveraging AI to build, read, and debug code (any language).

Preferred qualifications:

  • Experience leading projects or initiatives from design/concept through to delivery (e.g., driving a major feature improvement or new internal tool).
  • Ability to analyze and influence systems architecture and design patterns to improve supportability, debuggability, and diagnosability across the AI/ML product suite.
  • Ability to grow in changing environments and requirements.
  • Effective leadership and influencing skills in the application of AI or Machine Learning, with the ability to lead the design and implementation of AI-based solutions, web services, debugging tools, with a proven ability to work across Support and Product Engineering teams to align priorities and drive outcomes.

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.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: $150000 - $217000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Partner with Support, Engineering, and other cross-functional leadership to define and drive the roadmap for technical support innovation and agility across the AI/ML product portfolio.
  • Understand customer issues, advocate for their needs with internal teams, including product and engineering teams, to find ways to deliver support and products.
  • Resolve technical troubleshooting and mitigating complex systemic problems faced by our customers.
  • Design the future state of technical support and customer experience by defining and advocating new standards for support processes, telemetry, tooling, and operational readiness.
  • Oversee support launch readiness and excellence for new AI/ML products and identify targeted opportunities to transform the support experience.
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