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% in-region for meetings, technical reviews, and onsite delivery activities.
Minimum qualifications
Bachelor's degree in Computer Science or equivalent practical experience.
3 years of experience building machine learning solutions and working with technical customers.
Experience designing cloud enterprise solutions and supporting customer projects to completion.
Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
Experience coding in Python, including data structures, algorithms, and software design.
Ability to communicate in English fluently as this is a customer-facing role.
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.
Bachelor's degree in Computer Science or equivalent practical experience.
3 years of experience building machine learning solutions and working with technical customers.
Experience designing cloud enterprise solutions and supporting customer projects to completion.
Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
Experience coding in Python, including data structures, algorithms, and software design.
Ability to communicate in English fluently as this is a customer-facing role.
