Machine Learning Ops Lead

Description

Job Summary: Build the Machine Learning and MLOps infrastructure to develop, deploy, and maintain ML models in production, ensuring reproducibility and governance. Key Highlights: 1. Promoting financial inclusion in Venezuela with over 9 million users. 2. Work culture built on trust, purpose, and creativity. 3. Focus on real-world impact and ML team autonomy. Hello! We are Cashea, and our mission is to restore Venezuelans' access to credit through a BNPL business model. Since our launch in 2022, we have dedicated ourselves to advancing financial inclusion. Today, we serve over 9 million active users — both consumers and merchants — and have become a trusted brand in Venezuela, winning minds and hearts. #### **Role Summary** Build the Machine Learning and MLOps infrastructure enabling Data Scientists to develop, deploy, and maintain Machine Learning models in production following industry best practices. Responsible for creating tools, SDKs, and automated pipelines that ensure model reproducibility, observability, and governance — with an emphasis on self-service and ML team autonomy. Includes productionization and continuous improvement of complex models (Bayesian, ensembles) to enterprise-grade quality standards. #### **Responsibilities** * Build CLI tools for automated deployment (ml-deploy, ml-rollback) * Implement automated MLflow workflows (promotion: dev → staging → prod) * Create template repositories with best practices (model template, API template) * Establish best practices for Bayesian model productionization (sampling, inference, monitoring) * Document APIs and SDKs (Sphinx/MkDocs, tutorials, examples) * Conduct training sessions for Data Scientists (platform usage certification) * Develop self-service tools for Data Scientists (target: 80%+ autonomy) * Implement automated testing suites (model validation, performance checks) * Optimize Bayesian model performance in production (MCMC efficiency, inference speed) * Optimize MLflow performance (caching, query optimization) * Build monitoring dashboards for model health (accuracy, latency, convergence diagnostics) * Automate governance (approval gates, compliance checks) * Incident response & troubleshooting support * Maintain and evolve SDKs/tooling based on DS feedback * Improve serving architecture for complex models (Bayesian, ensembles) * Maintain continuous documentation (runbooks, troubleshooting guides) * Weekly office hours for Data Scientists (support + knowledge sharing) #### **Requirements** **Experience:** * 5+ years of experience in Data Science, Machine Learning, or MLOps * 2+ years working with MLOps tools in production (registry, tracking, model serving, monitoring, versioning) * Experience building internal Python SDKs/libraries * Experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) * Ability to understand Bayesian models, productionize them using best practices, and improve them **Technical Skills:** * Advanced Python (packaging, testing, documentation) * MLflow (registry, tracking server, model serving, artifacts) * Bayesian models (PyMC, Stan, or similar) — productionization and optimization * Basic Docker & Kubernetes * Git & GitHub/GitLab workflows * REST API design & development * Cloud platforms (GCP preferred; AWS/Azure acceptable) **Soft Skills:** * "Internal tooling" mindset (designing for fellow developers) * Clear and comprehensive documentation (technical writing) * Effective communication with Data Scientists (understanding their pain points) * Ownership and autonomy #### **Why You’ll Love Working at Cashea** At Cashea, we foster a work culture rooted in trust and purpose. If you’re wondering why we’re a great choice, here are our core values: * We don’t operate on autopilot. Everything we do is intentional. We love crafting ideas with full awareness of their potential impact on our users. * Your creativity and curiosity are your most valuable assets. * Your voice matters. We listen and make space for ideas and feedback. Everyone belongs — and what’s important to you is important to us too. * We value transparency. Clarity keeps us connected and grounded. * Last but not least, we focus on real-world impact. If you’d like to join us, please complete the application. We’d love to meet you!