Senior ML Platforms Engineer - MLOps on Azure Databricks

Wizeline; Ciudad de México; On-site; MXN 900,000 - 1,500,000; Full time

Benefits offered by this job

Professional development

Flexible culture

Total rewards

Job summary

Wizeline in CDMX is seeking an experienced ML Engineer/MLOps lead to architect end-to-end ML platforms and deploy models at enterprise scale. You will drive CI/CD with Azure Pipelines, MLflow, and Databricks, build governance, monitoring, and feature-registry strategies, and mentor other engineers.

You should have 5–8+ years in ML engineering, strong Spark, Databricks, Kubernetes, and Docker expertise, and the ability to operate across hybrid/multi-cloud environments.

Qualifications

• 5–8+ years in ML Engineering, MLOps, or high-scale ML systems.
• Proven track record deploying ML at enterprise scale with audit/monitoring layers.
• Familiarity with hybrid/multi-cloud infrastructure.

Responsibilities

• Architect end-to-end ML infrastructure across pipelines, serving, monitoring, and governance.
• Lead deployment of high-impact models (forecasting engines, NLP models).
• Design CI/CD workflows using Azure Pipelines, MLflow, and Databricks.
• Implement model registry, versioning, lineage, and audit compliance.
• Build monitoring systems for model drift and retraining automation.
• Mentor MLOps engineers and guide cross-functional platform integration.
• Drive adoption of MLOps best practices, from containerization to observability.
• Location: CDMX

Skills

ML Engineering

MLOps

Spark

Kubernetes

Docker

Tools

Azure Databricks

MLflow

Kubernetes

Docker

Azure Pipelines

Job description

Wizeline in CDMX is seeking an experienced ML Engineer/MLOps lead to architect end-to-end ML platforms and deploy models at enterprise scale. You will drive CI/CD with Azure Pipelines, MLflow, and Databricks, build governance, monitoring, and feature-registry strategies, and mentor other engineers.

You should have 5–8+ years in ML engineering, strong Spark, Databricks, Kubernetes, and Docker expertise, and the ability to operate across hybrid/multi-cloud environments.