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Salary
≈ $40k – $101k per year (Estimated)
Location
Hybrid (Mexico City, Mexico)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Apr 21, 2026. Wizeline scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Wizeline is a technology services company headquartered in San Francisco that provides nearshore software engineering, data and applied AI development, agentic delivery pods and AI advisory for enterprise clients in media and other industries. Founded in 2014 with deep roots in Mexico, it has a team of nearly 2,000 people across delivery hubs in Mexico City, Guadalajara, Barcelona, Bogota and Medellin plus offices in the US and Asia. Its openings include full-stack, backend and Java engineers, site reliability and data engineers, product managers and product designers, visual communicators, copy editors and marketing and print production project managers.

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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