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% for in-region for meetings, technical reviews, and onsite delivery activities.
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.
Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design.
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.
