DevOps (Gcp) Engineer, Airline Services - Monterrey, México - DataArt

DataArt

Empresa verificada

Monterrey, México

hace 3 semanas

Publicado por:

Rodrigo Fernández

Reclutador de talento para beBee

Descripción

Project overview:

The Advanced Analytics management is a transformational team within our client whose objective is to generate measurable value that lasts over time across all areas of the company.

To achieve this, custom data products are created based on analytical models, mostly from ML but being able to use a broader spectrum of techniques; either by delivering new analytical capabilities to the areas you work with or by directly interacting with your systems.

The development of the products and the associated change management is carried out using Agile methodologies (development) that incorporate the scientific method and LEAN tools (change management). To ensure the correct execution of our products, we work under a DevOps environment using the MLOps and DevOps SRE practices, guaranteeing the quality, security, and compliance of the company.
Responsibilities: Work directly with the ML Engineers team to put Machine Learning models into production using and creating ML pipelines
Implement DevOps SRE metrics
Administration and monitoring of team platforms
Responsible for the infrastructure and its proper functioning
To be the main promoter of practices and operationalization of the necessary pieces to serve our models and put them to interact with the rest of the company in a real environment and highly scalable
Promote a technical culture driving data products with DevOps, SRE and
MLOps
Requirements: At least 1 year of experience in work environments as Software Engineer, DevOps Engineer, SRE or ML Engineer
Experience with Python
Experience working in UNIX/LINUX environments
Experience creating CI/CD pipelines
Experience working with Docker
Experience in GIT
Intermediate/advanced oral and written English
Experience working with cloud services, preferably GCP
Excellent communication skills and collaborative work
Nice to have: Experience in Kubernetes
Experience designing and implementing automated tests
Experience in observability, monitoring
Understanding of the complete life flow of Machine Learning models
Experience in infrastructure as code, desirable Terraform
Experience with Jenkins
Agility to visualize possible improvements, problems, and solutions in Architecture
Experience with monitoring tools such as Grafana, Datadog, Nagios