About the company
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 worldās 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 1000+ teammates from 30+ different nationalities and developing an international career that impacts millions of peopleās 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.
Job Summary
What Will I Be Doing?
šCollaborate closely with cross-functional teams including data scientists, software engineers, and product managers to develop and improve scalable AI systems. šResearch, evaluate, and integrate new AI technologies, frameworks, and tools to improve payment systems' efficiency, security, and performance. šBuild and deploy AI solutions using a stack that features Python, LLM libraries, and AI third-party services and AWS services.
What Skills Do I Need?
šA Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. š+ 5 years of experience with Python programming language, LLM frameworks (Langchain, LlamaIndex), and interactive data apps (Streamlit, Gradio) šExperience with Docker. šExperience on applying scalability patterns (caching, parallelism, routing, asynchrony, decoupling, etc) šFamiliarity with Architecture for LLM Applications and Prompt Engineering techniques/patterns šExperience with DevOps best practices, including version control (Git), infrastructure as code (IaC), and continuous integration/continuous deployment (CI/CD) šExperience with Cloud infrastructure (AWS, Azure, or GCP)
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