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Googleposted about 1 month ago
$147,000 - $218,000/Yr
Full-time
San Francisco, CA
Web Search Portals, Libraries, Archives, and Other Information Services
Resume Match Score

About the position

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve business challenges, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks. You will engage with customers to understand business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You'll partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply your impact and the impact of the team as a whole. 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.

Responsibilities

  • Work with the team to identify and qualify business opportunities, understand key customer technical objections and develop the strategy to resolve technical blockers.
  • Provide in-depth machine learning expertise to support the technical relationship with Google's customers, including product and solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
  • Work with customers to demonstrate and prototype Google Cloud product integrations in customer/partner environments.
  • Recommend integration strategies, enterprise architectures, platforms and application infrastructure required to successfully implement a complete solution using best practices on Google Cloud.
  • Travel to customer sites, conferences, and other related events as required.

Requirements

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience with cloud native architecture in a customer-facing or support role.
  • 7 years of technical sales experience (i.e., working as a customer engineer, solutions engineer, or sales engineer).
  • Experience engaging with, and presenting to, technical stakeholders and executive leaders.

Nice-to-haves

  • Experience designing/architecting infrastructure farms for specialist AI use cases.
  • Experience training and fine tuning large models (i.e., image, language, segmentation, recommendation, genomics) with accelerators.
  • Experience with containerization, K8s, Kubernetes on cloud.
  • Experience with running MLPerf benchmarks.
  • Experience with performance profiling tools (i.e., Tensorflow profiler, PyTorch profiler, Tensorboard).
  • Ability to engage with C-level or executive business leaders and influence decisions.

Benefits

  • The US base salary range for this full-time position is $147,000-$218,000 + bonus + equity + benefits.
  • Our salary ranges are determined by role, level, and location.
  • Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Job Keywords

Hard Skills
  • Cloud Development
  • Cloud Solutions
  • Kubernetes
  • PyTorch
  • TensorFlow
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