Wizeline

Data Scientist - ML Engineering

Ciudad de Mexico

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hirly's read of this role

Role family: Data & ML
Seniority: Mid level
Country: MX
Work mode: On-site / unstated
First seen by hirly: 9 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

We are:

Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

With the right people and the right ideas, there’s no limit to what we can achieve

Are you a fit?

Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:

Key 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.

Must-have Skills

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 layers.

Familiarity with hybrid/multi-cloud infrastructure.

Nice-to-have:

AI Tooling Proficiency : Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.

Leadership experience in ML platform or DevOps teams.

Experience with feature stores and feature engineering. AutoML is a plus, H2O is a plus.

What we offer:

A High-Impact Environment

Commitment to Professional Development

Flexible and Collaborative Culture

Global Opportunities

Vibrant Community

Total Rewards

*Specific benefits are determined by the employment type and location.

Find out more about our culture here .

Original posting on Wizeline's site ↗

Listed on hirly, a job board. hirly is not the employer: Wizeline is hiring for this role.

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