Cloud Infrastructure Engineer for Airline Solutions

hace 1 mes


Montevideo, Montevideo, Uruguay DataArt A tiempo completo

Key Responsibilities

  • Collaborate closely with the Machine Learning Engineering team to deploy and manage Machine Learning models through the development of robust ML pipelines.
  • Establish and implement Site Reliability Engineering (SRE) metrics.
  • Oversee the administration and monitoring of team platforms.
  • Ensure the infrastructure operates effectively and efficiently.
  • Monitor and manage our applications to ensure optimal performance.
  • Act as the primary advocate for best practices and operationalization necessary for model deployment and interaction within a scalable production environment.
  • Foster a technical culture that promotes data product development through DevOps, SRE, and MLOps methodologies.

Required Qualifications

  • A minimum of 3 years of experience in roles such as Software Engineer, DevOps Engineer, SRE, or ML Engineer.
  • Proficiency in Python programming.
  • Experience working within UNIX/LINUX environments.
  • Skilled in creating Continuous Integration/Continuous Deployment (CI/CD) pipelines.
  • Familiarity with Docker for containerization.
  • Experience in deploying, managing, and scaling AI models and applications in production settings utilizing DevOps principles.
  • Proficient in version control using GIT.
  • Good command of spoken English.
  • Experience with cloud service platforms, preferably Google Cloud Platform (GCP).
  • Strong communication skills and ability to work collaboratively.

Preferred Qualifications

  • Experience with Kubernetes for container orchestration.
  • Background in designing and implementing automated testing frameworks.
  • Knowledge of observability and monitoring practices.
  • Understanding of the full lifecycle of Machine Learning models.
  • Experience with Infrastructure as Code, particularly with Terraform.
  • Familiarity with Jenkins for automation.
  • Aptitude for identifying potential improvements, challenges, and solutions in architectural design.
  • Experience with monitoring tools such as Grafana, Datadog, or Nagios.


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