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Worldly

ML Ops Engineer - Data Lake & AI Infrastructure

Reposted 20 Days Ago
Remote
Hiring Remotely in United States
145K-185K Annually
Mid level
Remote
Hiring Remotely in United States
145K-185K Annually
Mid level
The role involves designing and deploying a data lakehouse infrastructure, building ML pipelines, monitoring services, and collaborating with teams to optimize AI systems.
The summary above was generated by AI
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-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.

We'd Like to See
  • 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.

It Helps If You Have
  • 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.).

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

  • Unlimited PTO

  • 13 company holidays

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.

Benefits and Perks

  • 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

​​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

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.

Compensation Overview

Base Rate: $145,000 - $185,000 USD

Bonus: 10% Annually

Equity: Equity Stock Option Program

*Final compensation details will be determined based on a wide variety of factors, including experience and location. These factors will be evaluated and considered by Worldly throughout the entirety of this process.

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