ML Ops Engineer - Data Lake & AI Infrastructure
ML OPS ENGINEER - DATA LAKE & AI INFRASTRUCTURE
US - Remote
ABOUT WORLDLY
Worldly is the world’s most comprehensive impact intelligence platform — delivering real data to businesses on impacts within their supply chain. Worldly is trusted by 40,000 global brands, retailers, and manufacturers to provide the single source of ESG intelligence they need to accelerate business and industry transformation.
Through strategic and meaningful customer relationships, Worldly provides key insights into supplier performance, product impact, trends analysis, and compliance. When a company wants to change how business is done, we enable that systemic shift.
Backed by a dedicated global team of individuals aligned by values, Worldly proudly operates as a public benefit corporation with backing from mission-aligned investors. Want to learn more? Read our story
ABOUT THE ROLE
Worldly is the most comprehensive platform for measuring sustainability performance across the apparel, footwear, and consumer goods industries. We are rapidly expanding our data infrastructure and AI capabilities to help companies unlock insights, build credible sustainability claims, and power compliance with evolving regulations worldwide — all while managing complex global data challenges.
We’re looking for an MLOps Engineer to design, deploy, and support the next-generation data infrastructure and AI systems that unify structured and unstructured data at scale — across regions, including China.
WHAT YOU'LL DO
- Design and deploy data lakehouse infrastructure using open-source technologies (e.g., MinIO, Apache Iceberg, Trino) to ingest and manage high-volume structured and unstructured data.
- Build and scale ML pipelines using modern tools such as MLflow, LangChain/Haystack, and orchestrate them via Airflow or Dagster.
- Implement data ingestion and transformation workflows using tools like Apache NiFi, Airbyte, and dbt.
- Support federated querying and real-t...