Carla Jiménez, mlops engineer

Carla Jiménez

Senior MLOps Engineer

Madrid, Spain · Europe/Madrid (UTC+2) · 9 years of experience

Carla focuses on reproducible model delivery, promotion controls, observability, and rollback.

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Why this profile fits

Reproducible model delivery

Versions code, data references, configuration, and artifacts so training and promotion can be repeated and audited.

Safe promotion and rollback

Uses evaluation gates, staged rollout, lineage, and a tested rollback path for model changes.

Operational measurement

Monitors service health, data quality, drift, cost, and model behavior with clear ownership.

Relevant toolkit

PythonKubernetesMLflowTerraformCI/CD

Delivery evidence

Selected work

Geospatial Training Factory

mobility

Designed and delivered a production ML platform focused on geospatial model operations; standardized reproducible training across 14 city-specific demand models. The release included reproducible pipelines, promotion gates, lineage, drift alerts, and a documented rollback path.

PythonKubernetes

City Model Health Console

mobility operations

Built the supporting control and measurement layer for the primary system, covering review queues, regression checks, operational visibility, and a documented handoff to the owning team.

PythonTerraform
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Relevant experience

Career timeline

Senior MLOps Engineer

2023–Present

Devlyn client assignments · Remote

  • Led geospatial model operations delivery for a mobility team and standardized reproducible training across 14 city-specific demand models.

MLOps Engineer

2017–2022

mobility product company (confidential) · Madrid, Spain

  • Built production systems in mobility, with increasing ownership of reliability, testing, and stakeholder delivery.

Skill depth

Show experience in context.

VerbalCommunicationDomainUnderstandingProblemSolvingCodeQualitySystemDesignDeliverySpeed
Competency shapeAssessment across the same six dimensions used for every profile.

Relevant experience by skill

Python9 years
Kubernetes8 years
MLflow7 years
Terraform6 years
CI/CD9 years
Model Monitoring8 years
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Languages

PythonTypeScriptSQLBash

Frameworks

KubernetesMLflowTerraformKubeflowAirflowDocker

Tools

Argo CDPrometheusGreat ExpectationsGitHub ActionsDocker

Platforms

AWS SageMakerGoogle Vertex AIDatabricksKubernetes

Storage

S3Feature StoreDelta LakePostgreSQL

Paradigms

Model lifecycle automationGitOpsDrift monitoringReproducible training

Credentials

Certifications

AWS Certified Machine Learning Engineer – Associate

Amazon Web Services · 2023 · Certified

Databricks Certified Machine Learning Professional

Databricks · 2026 · Certified

Communication

Languages

English

Fluent

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