Cloud Ai Engineer, Professional Services, Google Cloud

**Minimum qualifications**:

- Bachelor's degree in Computer Science or equivalent practical experience.
- 6 years of experience building machine learning solutions and working with technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects to completion.
- Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design.
- Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
- Ability to communicate in English fluently as this is a customer-facing role.

**Preferred qualifications**:

- Experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost).
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
- Understanding of the auxiliary practical concerns in production machine learning systems.

**About the job**:
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

In this role, you will work with key Google 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 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**:

- Be a trusted technical advisor to customers and solve complex machine learning challenges.
- Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.