# Data Scientist - ML Engineering at WIZELINE

> Mexico · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Awizeline%3A7838717 (read 2026-11-08).

## Facts (observed)

- Company: [WIZELINE](https://alderhq.app/companies/wizeline)
- Location text: Ciudad de Mexico; Mexico
- Where it can be done from (inferred): Mexico (evidence: "Location: Ciudad de Mexico; Mexico")
- Posted: 2026-04-21 (201 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://www.wizeline.ai/careers/job?gh_jid=7838717
- Skills listed (inferred): Azure, Kubernetes, Docker, Spark

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

### 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.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Awizeline%3A7838717 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.