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Googleposted about 1 month ago
$125,000 - $183,000/Yr
Full-time
Los Angeles, CA
Web Search Portals, Libraries, Archives, and Other Information Services
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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'll work closely with technical sales teams as a subject matter expert in AI/ML to showcase the power of Google Cloud to our customers. You'll help both prospective and existing customers and partners understand the capabilities of Google Cloud, design creative solutions and architectures to address their business challenges, lead proofs of concept, and troubleshoot technical issues. You'll collaborate with internal engineering teams to improve products and build solutions that optimize results in production. You'll also find innovative ways to expand your impact and the team's overall success. You'll be part of a team of Googlers, working in an environment that fosters respect and opportunities for all. 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.
  • Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
  • Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
  • Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.
  • Travel to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.

Requirements

  • Bachelor's degree or equivalent practical experience.
  • 6 years of experience with cloud native architecture in a customer-facing or support role.
  • Experience engaging with, and presenting to, technical stakeholders and executive leaders.
  • Experience with Machine Learning model development and deployment.
  • Experience with frameworks for deep learning (e.g., PyTorch, Tensorflow, Jax, Ray, etc.) and using machine learning APIs.

Nice-to-haves

  • Master's degree in Computer Science, Engineering, Mathematics, a technical field, or equivalent practical experience.
  • Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks).
  • Experience in architecting and developing software or infrastructure for scalable, distributed systems.
  • Experience in data and information management.
  • Ability to learn quickly, understand, and work with new emerging technologies, methodologies, and solutions in the cloud/IT technology space.

Benefits

  • The US base salary range for this full-time position is $125,000-$183,000 + bonus + equity + benefits.
  • 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 Solutions
  • Machine Learning
  • PyTorch
  • Technical Issues
  • TensorFlow
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