Cloud AI Engineer, Professional Services
Please submit your resume in English - we can only consider applications submitted in this language.
- Bachelor's degree in Computer Science, Information Systems, related technical field, or equivalent practical experience.
- 8 years of experience building machine learning solutions.
- Experience coding in one or more languages: Python, Scala, Java, Go, or similar with competencies in data structures, algorithms, and software design.
- Experience working with technical customers.
- 10 years of experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with deep learning frameworks (such as TensorFlow, PyTorch, XGBoost).
- Experience in technical consulting.
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools and environments (Apache Beam, Hadoop, Spark, Hive).
- Understanding of the auxiliary practical concerns in production ML systems.
About the job
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you are the Google Engineer working with Google's largest and most ambitious Cloud customers. Together with the team you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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.
- Be a trusted technical advisor to customers and solve complex Machine Learning challenges.
- Create and deliver best practices recommendations, tutorials, blog articles, sample code, and technical presentations adapting to different levels of key business and technical stakeholders.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Coach customers on the practical challenges in ML systems: feature extraction/feature definition, data validation, monitoring, and management of features/models.
- Travel regularly (up to 30%, although we also frequently use video conferencing) in-person for meetings, technical reviews, and onsite delivery activities.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
At Google, we’re committed to building a workforce that is more representative of the users we serve and creating a culture where everyone feels like they belong. To learn more about our diversity, equity, inclusion commitments and how we’re building belonging, please visit our Belonging page for more information.
We welcome and encourage people who are expecting and/or parents-to-be to apply to this or any other role at Google.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles.
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