ML Ops Engineer - Data Lake & AI Infrastructure
About The Position
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.
Requirements
- 4+ years of experience in ML engineering, MLOps, or data infrastructure roles.
- Proven hands-on experience with containerized open-source data tools such as: Object stores: MinIO, Ceph, or HDFS Table formats: Apache Iceberg, Hudi, or Delta Lake Query engines: Trino/Presto, ClickHouse, or DuckDB Workflow orchestration: Airflow, Dagster, or Prefect ML tools: MLflow, LangChain, Hugging Face, or vLLM ETL/ELT tools: Airbyte, NiFi, dbt
- Experience managing infrastructure across multiple regions, including self-hosted deployments (Kubernetes, Docker Compose, Terraform, etc.).
- Experience monitoring ML prediction performance, drift metrics, and pipeline tools
- Strong understanding of data engineering best practices, including security, governance, and versioning.
Nice To Haves
- Experience deploying AI/ML infrastructure in China-compatible cloud environments (e.g., Alibaba Cloud, Huawei Cloud).
- Familiarity with retrieval-augmented generation (RAG) pipelines and unstructured document indexing.
- Exposure to 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.).
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.
- 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-time analytics via Trino, ClickHouse, or StarRocks.
- Enable retrieval-augmented generation (RAG) and other LLM-powered applications by integrating the data lake with AI/ML systems.
- Develop CI/CD pipelines for ML models, infrastructure-as-code, and data pipeline deployments.
- 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.
Benefits
- 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
- Unlimited PTO
- 13 company holidays
- Earn a competitive salary and performance-based bonuses. Get healthcare, retirement matching, and equity for US employees.
- Use the office stipend to get the supplies you need. Combat Zoom fatigue with Flex Fridays.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
101-250 employees
