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Key Responsibilities

  • Design and develop MLOps pipelines for model training, deployment, and retraining.
  • Containerize models using Docker and deploy via Azure Databricks or AKS.
  • Implement CI/CD workflows with MLflow and GitHub Actions.
  • Monitor model performance and data drift using Azure-native tools.
  • Collaborate with Data Scientists and Engineers to integrate models into business systems.
  • Document, standardize, and optimize ML deployment processes.

Must-have Skills

  • Bachelor's in Computer Science, Data Engineering, or a related field.
  • 2–4 years of experience in MLOps, ML Engineering, or DevOps for ML.
  • Proficient in Spark and MLflow; strong experience in Databricks and Azure ML.
  • Solid Python and SQL skills; knowledge of containers (Docker/Kubernetes).
  • Familiar with CI/CD concepts and tools like Azure DevOps or GitHub Actions.

Nice-to-have

  • Familiarity with Kubernetes (AKS), Terraform, and model observability practices.
  • Experience deploying Power BI dashboards that consume predictions.

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.

Job Summary

CompanyWIZELINE
Locationmexico
TypeFull-Time
LevelJunior
DomainAI / Data Science