
Cloud AI Developer, Google Cloud Consulting, PSO
- Toronto, ON
- Permanent
- Full-time
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Toronto, ON, Canada; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA.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 working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with deep learning frameworks (e.g., XGBoost).
- Understanding of the auxiliary practical concerns in production machine learning systems.
- 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, Flume).
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 $147,000-$216,000 + 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
- Become a trusted technical advisor to customers and solve complex machine learning tests.
- Coach customers on the practical tests 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% for in-region for meetings, technical reviews, and onsite delivery activities.