Customer Engineer II, AI/ML, Google Cloud
Job Summary
Job Description
As a Customer Engineer II, AI/ML, you will partner with technical Sales teams as a subject matter expert in AI/ML to differentiate Google Cloud to customers. You'll help prospective and existing customers understand Google Cloud, develop cloud solutions, engage in proofs-of-concept, and troubleshoot technical issues. You'll use expertise and presentation skills to engage with customers, understand their needs, and present solutions. You'll work with internal engineering stakeholders to improve products and build solutions, optimizing for results and identifying innovative ways to increase impact. Responsibilities include identifying business opportunities, resolving technical blockers, sharing AI/ML expertise, supporting bid responses, and working directly with Google Cloud products. You will also recommend integration strategies and travel to customer sites and conferences.
Must have:
- Bachelor's degree or equivalent experience
- 6+ years cloud native architecture experience
- Experience with ML model development & deployment
- Experience with deep learning frameworks (PyTorch, Tensorflow etc.)
- Excellent technical, communication & organizational skills
Good to have:
- Master's degree in technical field
- Experience building ML solutions and leveraging specific architectures
- Experience architecting software for scalable systems
- Experience in data and information management for big data
- Ability to quickly learn new technologies
Perks:
- Bonus
- Equity
- Benefits
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 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.
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 present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills. You will 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.
The US base salary range for this full-time position is $125,000-$183,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 .
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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