- Bachelor degree in Computer Science, Mathematics, or a related technical field, or equivalent practical experience.
- Experience writing software in one or more languages such as Python, Scala, R. Experience in data structures, algorithms, and software design.
- Experience building machine learning solutions.
- Experience working with technical customers.
- Experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with deep learning frameworks (e.g., Torch, Caffe, Theano).
- 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).
- Experience in technical consulting.
About the job
The Google Cloud Platform team helps 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 entrepreneurial team in this rapidly growing business, you will help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.
As a Cloud Machine Learning Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and CloudML Engine. 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. You will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products. In collaboration 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 helps millions of employees and organizations empower their employees, serve their customers, 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. And our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life.
- Be a 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.
- Travel within the region up to 30% for meetings, technical reviews, and onsite delivery activities.