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Job Description

Your Role:

The ML/MLOps Engineering team is responsible for architecting, deploying, and scaling enterprise AI/ML solutions while providing technical leadership, architectural guidance, and engineering best practices across the machine learning lifecycle. The team focuses on building reusable ML frameworks and platform capabilities, optimizing and refactoring large-scale PySpark workloads, tuning Spark cluster configurations for performance and cost efficiency, and enabling scalable, production-ready ML systems.



We are seeking a highly capable Senior MLOps Engineer with 6-10 years of experience in Software Engineering, MLOps, DevOps, Cloud Platforms, and Distributed Data Processing. The candidate will have proven experience collaborating directly with clients and stakeholders to gather requirements, define solution architectures, drive technical discussions, and deliver scalable, secure, and reliable machine learning platforms that accelerate business value and enterprise AI adoption.

Build Associate closely working with business stakeholders, data scientists, and engineering teams to understand business requirements and translate them into scalable AI/ML and data engineering solutions.
Lead technical discussions, solution design workshops, and architectural reviews to define end-to-end ML and MLOps implementation strategies.
Design, build, and maintain scalable, secure, and production-ready ML platforms and infrastructure across cloud environments.

📌 Senior Machine Learning Engineer (Bogotá)
🏢 Capgemini Engineering
📍 Bogotá