**Date:** Dec 5, 2025 **Location:** LIMA, Peru **Company:** Alicorp S.A.A. **What will be your challenge?** Design, implement, and maintain robust, scalable, and observable machine learning pipelines, models, and services—enabling analytical solutions to operate reliably, securely, and with measurable business impact—ensuring integration with corporate platforms and sustained adoption. **What will you do in this role?** * Ensure production deployment, operation, and continuous maintenance of machine learning models through reliable, secure, and versioned pipelines. * Design, develop, and optimize data and ML pipelines (training, inference, monitoring) using engineering best practices and automation. * Implement monitoring, observability, and alerts for models and infrastructure (e.g., drift, performance, latency, data quality). * Manage versioning of data, features, models, and experiments using MLOps tools (e.g., MLflow, Vertex AI, Feature Store). * Collaborate with Data Engineering, DevOps, and Product teams to ensure models and pipelines integrate with the Data Lake, APIs, business services, and frontends. * Document, standardize, and promote MLOps best practices (CI/CD, Infrastructure as Code [IaC], automated testing, governance). * Perform iterative improvements on production models based on metrics, operational feedback, and business changes. **What do we need from you?** * Bachelor’s degree in Systems Engineering, Computer Engineering, Statistics Engineering, Data Science, Software Engineering, or related fields. * Additional studies: Specialization in MLOps, DevOps, or Data Engineering; Machine Learning models and applied AI practices; CI/CD; Infrastructure as Code (IaC); Cloud architecture (GCP preferred); Observability, monitoring, and model governance; Agile methodologies oriented toward data products. * Languages: Intermediate English. * Software proficiency: Python, SQL, Power BI, BigQuery, MLflow, Feature Store, Docker, Kubernetes, Terraform, Git, CI/CD pipelines, and tools for ML/infrastructure drift detection, logging, and performance monitoring.