Google Cloud is looking to solve machine learning challenges for its customers and help businesses thrive by guiding them through their cloud journey
Requirements
Experience building machine learning solutions and working with technical customers
Experience designing cloud enterprise solutions and taking 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., 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
Responsibilities
Be a trusted technical advisor to customers and solve machine learning challenges
Coach customers on the practical challenges in machine learning systems such as 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
Design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI
Support customer implementation of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more
Travel to customer sites to deploy solutions and deliver workshops to educate and empower customers
Other
Bachelor's degree in Computer Science or equivalent practical experience
3 years of experience building machine learning solutions and working with technical customers
Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities
Work location and additional factors, including job-related skills, experience, and relevant education or training
Preferred working location from the following: Austin, TX, USA; Toronto, ON, Canada; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA
