Camille Zaug

Machine Learning Engineer @Ford Motor Company

CA, US

Analyzing and visualizing SQL, Hadoop, and BigQuery data sources to understand business practices, perform feature engineering, and determine model architecture to meet needs based on available data• Deploying internal Streamlit applications on Domino Data Lab to quickly share of data visualizations and/or application proof-of-concepts with both teammates and leadership• Modernizing high-impact analytics products by implementing the latest technologies and working with university partners to productionalize cutting edge data science research• Deploying containerized machine learning models by orchestrating Kubeflow training pipelines on Google Cloud Platform’s Vertex AI and scheduling batch jobs on Kubernetes • Constructing continuous integration/continuous deployment (CI/CD) Tekton pipelines on OpenShift• Practicing design thinking by collaborating with business partners to understand model strengths and weaknesses, enabling agile development practices to deliver fast improvements to the user experience• Collaborating cross-functionally with data scientists, engineers, and subject matter experts to make recommendations to business partners regarding areas of improvement in data collection and labeling• Learning new technologies by diving deep into internal and public documentation, benefiting from team knowledge, and quickly implementing test cases for hands-on practice• Developing team collaboration by documenting source code, contributing to shared team technical wiki, participating in technical knowledge shares, and organizing popular virtual team-building activities • Contributing to Ford\'s mission to become an Employer of Choice for women by working with Women of Ford to organize events for Women’s History Month and volunteering as a partner with Girls Who Code