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"description": "<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">At R2, we believe that small and medium businesses are the productive engine of society. Small and medium businesses (SMBs) make up over 90% of companies in Latin America, yet they face a trillion-dollar credit gap. Our mission is to unlock SMBs’ potential by providing financial solutions tailored to their needs. We are reimagining the financial infrastructure of Latin America, where SMBs’ financial needs are met without ever having to go to a bank.</span></p>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt\"><br>R2 enables platforms across Latin America to embed financial services that SMBs can leverage, starting with revenue-based financing. We are a high-performing, close-knit team with talent from organizations such as Google, Amazon, Nubank, Uber, Capital One, Mercado Libre, Globant, and J.P. Morgan. </span></p>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt\"><br>We are entering a new phase of growth following a strategic investment from Ant International, focused on rapidly expanding our partner footprint, strengthening our credit and underwriting capabilities, and scaling operations across multiple markets. As part of this growth journey, eligible team members have the opportunity to participate in R2’s Phantom Share Program, a performance-based incentive designed to align our team with the company’s long-term success and value creation. We believe in building a culture of ownership, where those who help create value share meaningfully in it.</span></p>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt\"><br>We are a data-first company. Machine Learning (ML) and Deep Learning (DL) are the core of our product, and data is the lifeblood for all of our decision-making. We are seeking a <span style=\"font-weight: bold\">Lead Machine Learning Engineer (Lead MLE) </span>to spearhead the design, development, and deployment of ML/DL models into production. As a Lead Machine Learning Engineer, you will own the end-to-end lifecycle of machine and deep learning systems at R2, from model deployment and monitoring to retraining, governance, and reliability in production. You will define the standards, tooling, and architectural patterns that allow data scientists and analysts to safely and efficiently ship models that directly power our credit and business decisions.</span></p>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt; font-weight: bold\"><br>What you’ll work on:<br><br></span></p>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Own ML systems & tooling in production :</span>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Define and evolve R2’s ML platform architecture, including model registries, feature pipelines, training infrastructure, and inference services.</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Evaluate and introduce tooling that improves developer velocity, reproducibility, and safety across the ML stack.</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Architect, implement, and deploy ML/DL models into production environments.</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Ensure models are optimized for scalability, latency, and reliability.</span></li>\n</ul>\n</li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Automate Monitoring & Maintenance:</span>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Design and build automated monitoring systems to track model performance, drift, and data quality of ML/DL models that consume data from various sources. </span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Establish alerting and retraining pipelines to maintain model performance and robustness sustainably over time .</span></li>\n</ul>\n</li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Automate Data Science processes:</span>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Develop frameworks to automate recurrent Data Science workflows (e.g. model evaluation, and retraining).</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Standardize best practices across the team for reproducibility and efficiency.</span></li>\n</ul>\n</li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Collaborate with technical teams & Lead other team members:</span>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Partner with Product, Engineering, and Risk teams to align ML/DL solutions to be productionized with business goals. Although you won’t be developing the models first hand initially, you will be involved with in-sample, out-of-sample, and production testing.</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Mentor junior and senior data scientists and analysts, fostering a culture of innovation, experimentation, and excellence.</span></li>\n</ul>\n</li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Research & Innovate in the MLOps spectrum:</span>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Stay ahead of emerging ML & DL production techniques and technologies, evaluating their applicability to organizational challenges.</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Drive experimentation and prototyping of novel production and automation approaches.</span></li>\n</ul>\n</li>\n</ul>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt; font-weight: bold\"><br>Who you are:<br><br></span></p>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have at least five (5) years of experience with machine and deep learning engineering in a practical setting</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have a good understanding of fintech products, and risk management to interpret business data effectively</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have strong programming abilities (structured, object-oriented, and/or event-oriented programming) and are comfortable programming in Python/R and SQL (with a focus on Snowflake, preferably)</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have strong proficiency in ML/DL frameworks in Python (e.g. Tensorflow, PyTorch, Scikit-learn)</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You are comfortable consuming data through APIs, SFTP, or straight-up CSVs</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You are experienced with MLOps tools (e.g. MLflow, Kubeflow, Docker, Kubernetes, AWS microservices)</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have a solid understanding of cloud platforms, preferably AWS, distributed computing, and version control using GitHub & GitLab</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have a strong understanding of model serving patterns (batch vs. online, synchronous vs. asynchronous)</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have experience designing feature pipelines with clear ownership, freshness guarantees, and backfills</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You understand data engineering practices for ETL pipelines development, and datawarehouses/datalakes management</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have a data-oriented mindset: you care about getting to the bottom of how to make decisions based on data</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">You have stakeholder management experience, keeping everyone up-to-date with key findings and explaining in a non-technical way results, methodologies and processes for data-driven decision making<br></span><br></li>\n</ul>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt; font-weight: bold\">To be considered a strong candidate, you:<br><br></span></p>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Are familiar with real-time ML systems.</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Have exposure to reinforcement learning, graph neural networks, or advanced time series techniques</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Have contributed to open-source ML/DL projects</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Have productionised A/B tests, multivariate tests, and other controlled experiments to assess the effectiveness of changes in product features, user experience, and marketing initiatives</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Have partnered with cross-functional teams to define key success metrics, ensuring alignment with business objectives</span></li>\n</ul>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt\"><br><span style=\"color: rgb(14, 14, 14); font-weight: bold\">What We Offer:<br></span><br></span></p>\n<ul>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">The chance to join a high-impact, mission-driven fintech with regional scale</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Leadership over enterprise controls for a fast-paced and growth-oriented startup</span></li>\n<li><span style=\"font-family: Inter, sans-serif; font-size: 12pt\">Cross-functional collaboration with exceptional teams across Latin America</span></li>\n<li><span style=\"color: rgb(14, 14, 14); font-family: Inter, sans-serif; font-size: 12pt\">Equipment provided by R2</span></li>\n<li><span style=\"color: rgb(14, 14, 14); font-family: Inter, sans-serif; font-size: 12pt\">Training budget for professional development</span></li>\n<li>Career growth within R2</li>\n</ul>\n<p><span style=\"font-family: Inter, sans-serif; font-size: 12pt\"><span style=\"font-weight: bold\"><br>Locations:</span> Buenos Aires, São Paulo, Santiago de Chile, Bogotá. </span></p>",
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