Senior ML Engineer & MLOps Architect for Enterprise AI

Wizeline; Ciudad de México; On-site; MXN 1,200,000 - 1,800,000; Full time

Benefits offered by this job

High-Impact Environment

Professional Development

Flexible Culture

Global Opportunities

Vibrant Community

Total Rewards

Location-based benefits

Job summary

Wizeline, a global AI-native technology solutions provider, seeks an experienced ML Engineer to architect end-to-end ML infrastructure, oversee enterprise-scale deployments, and drive MLOps practices across hybrid cloud environments.

You will design CI/CD workflows with Azure Pipelines, MLflow, and Databricks; mentor engineers; and accelerate the delivery of AI-powered products for clients worldwide.

Qualifications

• 5–8+ years in ML Engineering, MLOps, or high-scale ML systems.
• Deep expertise in Spark, Azure Databricks, MLflow, Kubernetes, and Docker.
• Proven track record deploying ML at enterprise scale with audit and monitoring.
• 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, optimization solvers, NLP models).
• Design advanced 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.

Skills

ML Engineering

MLOps

High-scale ML

Spark

Azure Databricks

MLflow

Kubernetes

Docker

Hybrid/Multi-cloud

Model deployment

Tools

Azure Pipelines

Databricks

Job description

Wizeline, a global AI-native technology solutions provider, seeks an experienced ML Engineer to architect end-to-end ML infrastructure, oversee enterprise-scale deployments, and drive MLOps practices across hybrid cloud environments.

You will design CI/CD workflows with Azure Pipelines, MLflow, and Databricks; mentor engineers; and accelerate the delivery of AI-powered products for clients worldwide.