Worldly
The ML Ops Engineer - Data Lake & AI Infrastructure at Worldly is responsible for designing, deploying, and supporting advanced data lakehouse infrastructure and AI systems that handle both structured and unstructured data at scale. Key responsibilities include building and optimizing ML pipelines using tools such as MLflow and orchestrating workflows with Airflow, implementing data ingestion and transformation processes, and enabling real-time analytics. The role requires collaboration with various teams to create scalable MLOps solutions while managing infrastructure across multiple regions, particularly in China. Candidates should have a strong background in ML engineering and experience with open-source data tools and practices.
Headquarters
Concord, California, United States
Company Size
51-200 employees
Founded
2019
Worldly is a leading sustainability data and analytics platform designed for retail and consumer goods companies. It provides tools and insights that help brands and manufacturers track supply chain performance, manage social and environmental impacts, and fulfill sustainability reporting requirements. With a focus on empowering stakeholders with rich data and efficient workflows, Worldly aims to simplify sustainability efforts and drive measurable progress across the industry. The platform facilitates supplier engagement, risk management, and regulatory compliance through its extensive network of suppliers.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Worldly.
Worldly Acquires Apparel Sector Sustainability Data Platform GoBlu
Oct 9, 2025