Customer Engineer, AI/ML Technical Sales, Google Cloud
Job Summary
Job Description
- Bachelor's degree or equivalent
- 6+ years cloud native architecture experience
- ML model development & deployment experience
- Deep learning framework experience (PyTorch, TensorFlow etc.)
- Excellent communication skills
- Master's degree in technical field
- Experience building ML solutions
- Experience with scalable, distributed systems
- Big data experience
- Ability to quickly learn new technologies
6 skills required
Job Details
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 6 years of experience with cloud native architecture in a customer-facing or support role.
- 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.
- Experience engaging with, and presenting to, technical stakeholders and executive leaders with the ability to communicate fluently in English.
Preferred qualifications:
- 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 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 partner with Technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business challenges, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud.
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.
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