Location: Mexico (100% Remote) Project: (6-8 months) We are seeking a highly experienced Machine Learning Engineer to join our MarTech team and play a pivotal role in driving innovation within our ML ecosystem. You will be responsible for the end-to-end development, optimization, and deployment of production-ready ML models and feature engineering pipelines, with a strong emphasis on operationalizing models that power the customer experience. This role demands a strong understanding of ML engineering best practices and proven experience building scalable ML systems and feature pipelines. Responsibilities: o Design, develop, and deploy machine learning solutions and feature engineering pipelines. o Configure, test, debug, deploy, document, and maintain ML pipelines, models and feature engineering modules while adhering to specific development best practices and quality standards. o Work closely with data scientists, data engineers, and solution architects to develop technical design specifications for ML programs, focusing on efficient feature engineering and model deployment.



o Analyze large-scale datasets and validate the proposed ML solutions with both the architectural design and the business needs, ensuring model performance meets target metrics. o Responsible for troubleshooting and issue analysis across the ML stack, including feature pipelines, model training, inference, and model monitoring, as well as coding, testing, and implementing model enhancements. o Demonstrate a strong understanding of supervised, unsupervised, ensemble, and deep learning algorithms to design and implement effective ML solutions, with experience in feature engineering, model evaluation, and continuous performance optimization to meet business targets. o Implement and maintain MLOps practices including experiment tracking, model versioning, A/B testing, and automated retraining pipelines. o Thrive in a fast-paced agile development environment, driving iterative model improvements. o

📌 MLOps Engineer (México)
🏢 Valce Talent Solutions
📍 México