ML Ops Engineer - Data Lake & AI Infrastructure

• Design and deploy data lakehouse infrastructure using open-source technologies to ingest and manage high-volume structured and unstructured data
• Build and scale ML pipelines using modern tools and orchestrate them via workflow systems
• Implement data ingestion and transformation workflows using ETL/ELT tools
• Enable retrieval-augmented generation (RAG) and other LLM-powered applications by integrating the data lake with AI/ML systems

This role helps companies unlock insights, build credible sustainability claims, and power compliance with evolving regulations worldwide by building the data infrastructure and AI systems that enable systemic shifts in how business is done.

• 4+ years of experience in ML engineering, MLOps, or data infrastructure roles
• Proven hands-on experience with containerized open-source data tools including object stores, table formats, query engines, workflow orchestration, ML tools, and ETL/ELT tools
• Experience managing infrastructure across multiple regions, including self-hosted deployments
• Strong understanding of data engineering best practices, including security, governance, and versioning

• Base salary: $145,000 - $185,000 USD with 10% annual bonus and equity stock options
• Comprehensive benefits with 90% employee premium and 75% spouse/dependent premium covered
• Company-sponsored 401k with up to 4% match
• 100% Parental Paid Leave
• Unlimited PTO and 13 company holidays
• Flexible remote work with office stipend and Flex Fridays
• Remote team culture with various interest groups and activities

Worldly is the world's most comprehensive impact intelligence platform that delivers real data to businesses on impacts within their supply chain, trusted by 40,000 global brands, retailers, and manufacturers to provide ESG intelligence needed to accelerate business and industry transformation.