Data Scientist - ML Engineering
At Wizeline · Ciudad de Mexico; Mexico
- Data and ML
- Full-time
Where you’ll work
Hybrid, based in Mexico City
“Ciudad de Mexico”
From the location.
“Mexico”
From the job board field.
“Familiarity with hybrid/multi-cloud infrastructure.”
From the job description.
Hybrid means some days in the office. The listing says how many, and where.
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- Posted
- 21 April 2026
- First seen by us
- 9 October 2026
- Last checked
- 10 hours ago
Job description
From Wizeline’s job post, as they wrote it.
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
Read the full description
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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