AI Engineer, Google Cloud Customer Experience

This role may also be located in our Playa Vista, CA campus.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Atlanta, GA, USA; Boulder, CO, USA; Cambridge, MA, USA; Chicago, IL, USA; Houston, TX, USA; New York, NY, USA; Los Angeles, CA, USA; Reston, VA, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA; Miami, FL, USA; Addison, TX, USA.

Minimum qualifications:

• Bachelor’s degree in Computer Science, Mathematics, or a related technical field, or equivalent practical experience.
• Experience in building machine learning (ML) solutions.
• Experience coding in one or more languages (e.g., Python, Scala, Java, Go, or similar) with experience in data structures, algorithms, and software design.
• Experience working with technical customers.

Preferred qualifications:

• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• Experience in technical consulting.
• Experience with deep learning frameworks (e.g., l, Torch, Caffe, Theano).
• Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, extract transform load (ETL), and reporting or analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).

• Understanding of the auxiliary practical concerns in production ML systems.

About the job

The Google Cloud Platform team helps customers transform and build what’s next for their business — all with technology built in the cloud. Our products are engineered for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, businesses, educational institutions, and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

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, travel to customer sites to deploy solutions, and deliver workshops to educate and empower customers. Additionally, you will work with Product Management and Product Engineering to build and constantly lead excellence in our products.

Google Cloud accelerates organizations’ ability to digitally transform their business with 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.

The US base salary range for this full-time position is $107,000-$163,000 + 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 for new hire 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

• Become a trusted technical advisor to customers and solve Machine Learning challenges.
• Create and deliver best practices recommendations, tutorials, blog articles, sample code, and technical presentations adapting to different levels of business and technical stakeholders.
• Work with customers, partners, and Google Product teams to deliver tailored solutions into production.
• Mentor customers on the practical challenges in ML systems, including feature extraction, feature definition, data validation, monitoring, and management of features or models.
• Travel in-region up to 30% of the time 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 and If you have a disability or special need that requires accommodation, please let us know by completing our .