ML Ops Engineer

Why should you join dLocal?

dLocal enables the biggest companies in the world to collect payments in 40 countries in emerging markets. Global brands rely on us to increase conversion rates and simplify payment expansion effortlessly. As both a payments processor and a merchant of record where we operate, we make it possible for our merchants to make inroads into the world’s fastest-growing, emerging markets. 

By joining us you will be a part of an amazing global team that makes it all happen, in a flexible, remote-first dynamic culture with travel, health, and learning benefits, among others. Being a part of dLocal means working with 900+ teammates from 25+ different nationalities and developing an international career that impacts millions of people’s daily lives. We are builders, we never run from a challenge, we are customer-centric, and if this sounds like you, we know you will thrive in our team.

What’s the opportunity? Design and build large scale architectures, workflows, tools and automation for processing data and apply machine learning engineering to solve global business challenges with focus on making tasks easier for data scientists.

What will I be doing?

• Architect and develop end to end machine learning solutions.
• Manage and automate machine learning lifecycle.
• Collaborate with data engineers and data scientists to create highly scalable solutions.
• Work on cloud solutions, evaluating the performance and cost of potential architectures.
• Understand the software development life cycle to collaborate and integrate solutions with other technical areas.
• Interact with other teams to understand business challenges and propose solutions.
• Communicate and teach on how to use the developments.

What skills do I need?

• Bachelor’s degree in software engineering/computer science or proven experience in data engineering or machine learning roles.
• Proven experience implementing and deploying machine learning solutions.
• Advanced knowledge of Python, SQL and Spark.
• Knowledge in some of the following tools or similar technologies: Docker, Git, Bash Scripting, FastAPI, Sagemaker Studio, Airflow, Cloudformation.
• Knowledge of data architectures and systems integration.
• Ability to solve complex software system issues.
• Experience with cloud platforms like AWS and GCP.
• Experience in payments or other financial systems is a plus.
• Team player – can effectively participate as an effective team member.
• Curious profile, self learner and positive attitude.
• Good communication skills.