Customer Engineer III, AI/ML, Central, Google Cloud Full-time

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience as a sales engineer or technical consultant in a cloud computing environment or in a customer-facing role.
• Experience in virtualization or cloud native architectures in a support role.
• Experience with big data, machine learning, and numerical programming frameworks (e.g., TensorFlow, Python, MATLAB).
• Experience using an AI platform to build, deploy, and manage machine learning models.

Preferred qualifications:

• Master’s degree in Computer Science or a related technical field.
• Experience building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks).
• Experience architecting and developing software or infrastructure for scalable distributed systems.
• Experience in data and information management as it relates to big data trends and issues within businesses.
• Ability to learn quickly, understand, and work with new emerging technologies, methodologies, and solutions in the cloud/IT technology space.

About the job

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 work with Technical Sales teams as a machine learning subject matter expert to differentiate Google Cloud to our customers. In this role, 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. Additionally, you will have the opportunity to help customers to leverage specialized Machine Learning (ML) hardware developed by Google (e.g., Tensor Processing Unit). You will also work closely with customers and product development to shape the TPU platform.

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.

The US base salary range for this full-time position is $142,000-$214,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• Work with the team to identify and qualify business opportunities, understand key customer technical objections and develop the strategy to resolve technical blockers.
• Work with customers to demonstrate and prototype Google Cloud product integrations in customer/partner environments.
• Recommend integration strategies, enterprise architectures, platforms and application infrastructure to implement a complete solution using best practices on Google Cloud.
• Travel to customer sites, conferences, and other related events as needed.
• 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.