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ML Ops with GCP

UrpanTech

 

Houston, TX, USA

Posted On: 1 day ago
Experience: 10+ years
Availability: Onsite
Openings: 1
Category: ML Ops
Tenure: No Preference/Any
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Description

You will own the operationalization of machine learning systems on Google Cloud Platform.

This role is hybrid.

Responsibilities

  • Design and implement end-to-end ML pipelines using Vertex AI Pipelines, Cloud Functions, and Cloud Composer.
  • Automate ML model training, evaluation, deployment, and monitoring in production environments.
  • Manage CI/CD pipelines for ML workflows using Cloud Build, GitHub Actions, or Jenkins.
  • Build and manage scalable infrastructure using Infrastructure as Code tools like Terraform or Deployment Manager.
  • Monitor model performance, data drift, and system reliability using Vertex AI Model Monitoring, Prometheus, and Grafana.

Required Skills

  • 10+ years of professional experience in ML Operations.
  • Expertise with GCP services, including Vertex AI and AI Platform Prediction.
  • Experience building and managing CI/CD pipelines.
  • Proficiency with monitoring stacks such as Prometheus and Grafana.
  • Ability to implement Infrastructure as Code (IaC) using Terraform or Deployment Manager.
  • Experience managing model versioning and lineage using ML Metadata and Artifact Registry.
  • Familiarity with Docker-based ML deployments.

Preferred Skills

  • Any Graduate degree.

Education

Any Graduate

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