Worldly - ML Ops Engineer - Data Lake & AI Infrastructure
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Requirements
• Experience deploying AI/ML infrastructure in China-compatible cloud environments (e.g., Alibaba Cloud, Huawei Cloud). • China-compatible cloud environments • Familiarity with retrieval-augmented generation (RAG) pipelines and unstructured document indexing. • retrieval-augmented generation (RAG) • Exposure to sustainability or supply chain data models. • sustainability or supply chain data models • Contributions to open-source data or MLOps projects. • Experience supporting data quality pipelines and/or data privacy frameworks (GDPR, CSRD, etc.). • data quality pipelines • data privacy frameworks • What We Can Offer You • Comprehensive benefits offerings. 90% employee premium and 75% spouse/dependent premium covered by Worldly. • Company-sponsored 401k with up to 4% match. • Incentive Stock Options • 100% Parental Paid Leave • 13 company holidays • Life at Worldly • Life at Worldly • Our team is motivated to transform the way products are made. By helping our customers succeed in a new era of sustainable production, we can build technology that makes a difference on a planetary level. • Our team represents over 15 countries and brings unique experiences from technology to farming to the table. Surround yourself with kind, enthusiastic, and dedicated people who put collaboration and growth at the center of our shared goals.
Responsibilities
• 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. • Design and deploy data lakehouse infrastructure • Build and scale ML pipelines using modern tools such as MLflow, LangChain/Haystack, and orchestrate them via Airflow or Dagster. • Build and scale ML pipelines • Implement data ingestion and transformation workflows using tools like Apache NiFi, Airbyte, and dbt. • Implement data ingestion and transformation workflows • Support federated querying and real-time analytics via Trino, ClickHouse, or StarRocks. • Support federated querying and real-time analytics • Enable retrieval-augmented generation (RAG) and other LLM-powered applications by integrating the data lake with AI/ML systems. • Enable retrieval-augmented generation (RAG) • Develop CI/CD pipelines for ML models, infrastructure-as-code, and data pipeline deployments. • Develop CI/CD pipelines • Monitor, debug, and optimize data and ML services running across distributed environments (including mainland China). • Collaborate cross-functionally with data scientists, platform & DevOps engineers, and sustainability analysts to translate real-world use cases into scalable MLOps workflows. • We'd Like to See • We'd Like to See • 4+ years of experience in ML engineering, MLOps, or data infrastructure roles. • ML engineering • MLOps • data infrastructure roles • Proven hands-on experience with containerized open-source data tools such as: • containerized open-source data tools • Object stores: MinIO, Ceph, or HDFS • MinIO • Table formats: Apache Iceberg, Hudi, or Delta Lake • Apache Iceberg • Query engines: Trino/Presto, ClickHouse, or DuckDB • Trino/Presto • ClickHouse • Workflow orchestration: Airflow, Dagster, or Prefect • Airflow • Dagster • ML tools: MLflow, LangChain, Hugging Face, or vLLM • MLflow • LangChain • Hugging Face • ETL/ELT tools: Airbyte, NiFi, dbt • Airbyte • Experience managing infrastructure across multiple regions, including self-hosted deployments (Kubernetes, Docker Compose, Terraform, etc.). • multiple regions • self-hosted deployments • Experience monitoring ML prediction performance, drift metrics, and pipeline tools • Strong understanding of data engineering best practices, including security, governance, and versioning. • data engineering best practices
Benefits
• $145K – $185K • Offers Equity • Offers Bonus • 10% Annual Bonus • ML Ops Engineer - Data Lake & AI Infrastructure • 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. • 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. • MLOps Engineer • Earn a competitive salary and performance-based bonuses. Get healthcare, retirement matching, and equity for US employees. • Use our work-from-home stipend to get the supplies you need. • Flexible time off. Take the time you need to recharge. Our culture encourages team members to explore and rest to be their best selves. • We're remote, not lonely. Join the culture committee, coffee chats, or a variety of other interest groups. • Travel Notice • Travel Notice • Roles at Worldly may require occasional travel to support business needs, including but not limited to team collaboration, customer engagement, or company events. • Equity Statement • Equity Statement • We believe it’s essential to reflect the diversity of those we strive to serve. True innovation happens when everyone has room at the table, including the tools, resources, and opportunity to excel. We’re dedicated to building a culturally and experientially diverse team that leads and works with empathy and respect.
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