dLocal started with one goal – to close the payments innovation gap between global enterprise companies, and customers in emerging economies. We have over 1000 payment methods, in more than 60 countries. We are relentlessly focusing on serving our customers and solidifying our position as the preferred infrastructure solution for Global Merchants across Emerging Markets. With the ability to accept local payment methods and facilitate cross-border fund settlement worldwide, our merchants reach billions of underserved consumers in the high-growth markets of Africa, Asia, and Latin America. dLocal offers the ideal payment solutions for integral commerce.
- Payins: Accept local payment methods
- Payouts: Compliantly send funds cross-border
- dLocal for Platforms: Unify your platform’s payment solution
- Defense Suite: Manage fraud effectively
Financial technology for markets of the future.
We’re looking for an
MLOps Technical Referent
to serve as the senior technical reference for how we build, operate, and evolve our ML and AI infrastructure.
Your mission is to enable Data Science and AI teams to take models and AI-powered services from idea to production in a reliable, observable, and compliant way. You will own the technical direction of our MLOps stack, introduce AI safely into our engineering workflows, and help the team scale its impact as usage and complexity grow.
A core part of this role is to use agents and AI services to automate as much as possible of what we do in MLOps — from feature store and platform operations to fraud/anomaly workflows and ML cost optimization — working side by side with the AI team. This is a hands-on architecture and leadership role: you won’t own product models yourself, but you will deeply influence how every model and AI component is trained, deployed, monitored, and run in production.
What will I be doing?
- Technical Strategy & Architecture: Define and evolve the end-to-end ML platform architecture (data, trainin
📌 ML Ops Staff Engineer (Barcelona)
🏢 dLocal
📍 Barcelona
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