Customer Engineer II, AI/ML, Startups, Google Cloud

2 Months ago • 6 Years + • Artificial Intelligence • $122,000 PA - $180,000 PA

Job Summary

Job Description

As a Customer Engineer II, AI/ML, you'll partner with technical sales teams to differentiate Google Cloud to startups. Responsibilities include sharing AI/ML expertise, supporting bid responses, creating proof-of-concept work, and directly partnering with product management. You will work directly with Google Cloud products, recommend integration strategies, and travel to customer sites and conferences. You'll help customers understand Google Cloud's power, develop cloud solutions, and troubleshoot technical issues. The role requires strong collaboration with internal teams and external stakeholders to optimize solutions and identify innovative ways to maximize impact. This position necessitates a deep understanding of machine learning model development and deployment within cloud-native architectures.
Must have:
  • 6+ years cloud native architecture experience
  • Machine learning model development & deployment
  • Experience with startups and Greenfield territories
  • Technical stakeholder and executive presentations
  • Google Cloud product expertise
Good to have:
  • Experience architecting scalable, distributed systems
  • Building ML solutions using specific architectures (neural networks, LLMs)
  • Proficiency in deep learning frameworks (PyTorch, TensorFlow, Jax, Ray)
  • Experience with ML APIs
  • Big data management expertise
Perks:
  • Bonus
  • Equity
  • Benefits

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.

Preferred qualifications:

  • Experience in architecting and developing software or infrastructure for scalable, distributed systems.
  • Experience in building Machine Learning (ML) solutions and leveraging specific Machine Learning architectures (e.g., neural networks, Large Language Models (LLM) and MLOps)).
  • Experience with frameworks for deep learning (e.g., PyTorch, Tensorflow, Jax, Ray, etc.) and using Machine Learning Application programming interfaces (API).
  • Experience in data and information management as it relates to big data trends and issues within businesses.
  • Experience engaging with, and presenting to, technical stakeholders and executive leaders.
  • Experience working with, and passion for, the startup ecosystem and building out Greenfield territories.

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.

Google Cloud empowers startups to address critical needs in scaling, growth, and global expansion, while offering advanced technologies that drive differentiation, customer acquisition, and business acceleration. 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 across the startup ecosystem. You will help customers and partners understand the power of Google Cloud, develop creative cloud solutions to solve business challenges, engage in proofs of concepts, and troubleshoot technical questions and roadblocks. You will engage with customers to understand their business and technical requirements, and present practical and useful solutions on Google Cloud. In addition, you will partner with engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply impact.

You will be a part of a diverse team of fellow Googlers working in an environment of respect and inclusion where we promote equal opportunities to succeed.

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 $122,000-$180,000 + 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 .

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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