Senior MLOps Engineer - Scale Enterprise AI Platforms

Capgemini Engineering; Colombia; Presencial; COP 120.000.000 - 190.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Stable Employment

Learning & Development

Language Training

Health Coverage

Insurance Protection

Wellness Perks

Descripción de la vacante

Capgemini Engineering in Colombia is seeking a Senior MLOps Engineer with 6–10 years of experience in software engineering, MLOps, DevOps, cloud platforms, and distributed data processing to architect, deploy, and scale enterprise AI/ML solutions while guiding stakeholders.

You will work with data scientists and engineers to design reusable ML frameworks, optimize PySpark workloads, setup CI/CD pipelines, and deliver secure, production-ready ML platforms across cloud environments.

Formación

• Masters in computer science, data science, data engineering or a related field.
• 6-10 years of experience in Data Engineering or MLOps.
• Strong hands-on experience with PySpark optimization and cluster performance tuning.
• Experience with Azure Databricks, Apache Spark, Azure Machine Learning and Azure DevOps.
• Proficiency in Python, SQL and CI/CD tools.
• Experience with Agile Software Development.
• Proven experience in developing and deploying supervised ML models, pricing and billing recommendation systems.
• Experience building production-grade ML pipelines and enterprise AI platforms.
• Strong client-facing communication skills with experience gathering requirements and stakeholder management.

Responsabilidades

• Build associates closely with business stakeholders, data scientists, and engineering teams to translate requirements into scalable AI/ML solutions.
• Lead technical discussions, design workshops, and architectural reviews for end-to-end ML and MLOps implementations.
• Design, build, and maintain scalable, secure, production-ready ML platforms across cloud environments.
• Develop reusable frameworks, templates, and best practices to accelerate model development and deployment.
• Optimize and refactor large-scale PySpark applications for performance and cost efficiency.
• Configure, tune, and manage Spark clusters including executor sizing and resource allocation.
• Design and maintain CI/CD pipelines for automated model training, testing, deployment, and monitoring.
• Establish MLOps best practices including version control, experiment tracking, model registry, governance, and reproducibility.

Conocimientos

PySpark optimization

Python

SQL

CI/CD

Cloud platforms

Client-facing communication

Apache Spark

Educación

Masters in computer science/data science/data engineering

Herramientas

Azure Databricks

Apache Spark

Azure Machine Learning

Azure DevOps

CI/CD pipelines

Descripción del empleo

Capgemini Engineering in Colombia is seeking a Senior MLOps Engineer with 6–10 years of experience in software engineering, MLOps, DevOps, cloud platforms, and distributed data processing to architect, deploy, and scale enterprise AI/ML solutions while guiding stakeholders.

You will work with data scientists and engineers to design reusable ML frameworks, optimize PySpark workloads, setup CI/CD pipelines, and deliver secure, production-ready ML platforms across cloud environments.