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Sales Engineer, Machine Learning, Google Cloud 280 views

Minimum Qualifications

    • Bachelor’s degree in Computer Science or Electrical Engineering, or equivalent practical experience.
    • Experience presenting and delivering technical pitches.
    • Experience with big data and machine learning frameworks, as well as numerical programming frameworks.

Preferred Qualifications

    • Master’s degree in Computer Science or other technical fields.
    • Experience in data and information management.
    • Experience with building machine learning solutions and leveraging specific machine learning architectures (e.g. deep learning, LSTM, convolutional networks, etc).
    • Experience architecting and developing software or infrastructure for scalable, distributed systems.
    • Ability to quickly learn, understand and work with new emerging technologies, methodologies, and solutions in the Cloud/IT technology space.

About The Job

The Google Cloud Platform team helps customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an entrepreneurial team in this rapidly growing business, you will help shape the future of businesses of all sizes use technology to connect with customers, employees, and partners.

As a Sales Engineer for Machine Learning, you will work hand-in-hand with technical Sales teams as a machine learning subject matter expert to differentiate Google Cloud to their customers. You will help prospective customers and partners understand the power of Google Cloud, explaining technical features, helping customers design architectures, and problem-solving any potential roadblocks. You will also have the opportunity to help customers to leverage specialized machine learning (ML) hardware developed by Google (e.g., Tensor Processing Unit). In this role, you will work closely with customers and product development to shape the TPU platform.

Google Cloud helps millions of employees and organizations empower their employees, serve their customers, and build what’s next for their business — all with technology built in the cloud. Their products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. And their teams are dedicated to helping their customers and developers see the benefits of their technology come to life.

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 hands-on 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.

At Google, they don’t just accept difference—they celebrate it, they support it, and they thrive on it for the benefit of their employees, products, and community. Google is proud to be an equal opportunity workplace and is an affirmative action employer. They 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. They 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 them know by completing this form.

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