Senior MLOps Engineer: Scalable ML Pipelines & Deployment

LORE; Colombia; A distancia; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

LORE is seeking an MLOps engineer who thrives at the intersection of machine learning, infrastructure, and production systems. This hands-on role focuses on turning prototypes into scalable, reliable, and compliant deployments, with emphasis on pipelines, automation, and observability.

You will work with ML engineers, software and data teams to productionize models in real-time systems, implement governance and reproducibility, and design cloud-native ML infrastructure.

Formación

• MS or higher in Computer/Information Science, Engineering, Mathematics, or related field.
• 8+ years of experience building and maintaining production ML systems or 5+ years MLOps with strong industry track record.
• Strong Python proficiency including testing and version control.
• Hands-on cloud platform experience and ML infrastructure expertise.

Responsabilidades

• Build tools, templates, and resources so ML engineers can own end-to-end ML systems—from development environments to production deployment and monitoring.
• Design, build, and maintain reliable ML pipelines for data ingestion, training, evaluation, deployment, and monitoring.
• Collaborate with ML engineers, software engineers, and data engineers to productionize models and embed them into real-time systems.
• Establish and improve MLOps standards, tooling, automation, CI/CD, reproducibility, and documentation.
• Implement robust model governance: lineage, versioning, auditability, compliance, and safe-deployment practices.
• Set up and maintain cloud-native ML infrastructure including storage, compute, orchestration, and security.
• Evaluate and integrate emerging technologies in the MLOps ecosystem to improve velocity, safety, and quality.
• Communicate technical concepts clearly with cross-functional and non-technical teams.

Conocimientos

Python

CI/CD

Airflow

Prefect

Cloud platforms

Model deployment

Docker

Monitoring

Data pipelines

Version control

Educación

Master's degree in Computer Science, Engineering, or related field

Herramientas

Airflow

Prefect

Cloud Composer

Docker

Kubernetes

Descripción del empleo

LORE is seeking an MLOps engineer who thrives at the intersection of machine learning, infrastructure, and production systems. This hands-on role focuses on turning prototypes into scalable, reliable, and compliant deployments, with emphasis on pipelines, automation, and observability.

You will work with ML engineers, software and data teams to productionize models in real-time systems, implement governance and reproducibility, and design cloud-native ML infrastructure.