Google Cloud Platform Infrastructure Data Engineer

  • Somerset, NJ
  • Posted 4 hours ago | Updated 4 hours ago

Overview

Remote
On Site
Hybrid
$70 - $100
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 36 Month(s)
Able to Provide Sponsorship

Skills

Ansible
Artificial Intelligence
Bash
Cloud Computing
Cloud Storage
Collaboration
Continuous Delivery
Continuous Integration
Data Engineering
Data Science
DevOps
Docker
GitLab
Good Clinical Practice
Kubernetes
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Google Cloud
Google Cloud Platform
Provisioning
Python
Information Security Governance
Jenkins
Management
Network Security
Orchestration
Terraform
Vertex

Job Details

We are seeking a highly skilled Google Cloud Platform Infrastructure & Automation Engineer with expertise in Vertex AI to design, implement, and manage scalable, secure, and automated cloud environments. The role involves working closely with data science, MLOps, and DevOps teams to support machine learning workflows, model deployment, and end-to-end automation on Google Cloud.

Key Responsibilities:

  • Design, deploy, and maintain Google Cloud Platform infrastructure for ML and AI workloads using Terraform, Deployment Manager, or similar IaC tools.

  • Build and manage CI/CD pipelines for ML models and applications on Vertex AI.

  • Automate environment provisioning, monitoring, and scaling for AI/ML workloads.

  • Collaborate with Data Science teams to streamline data pipelines and model deployment processes.

  • Implement MLOps best practices for training, testing, and deploying models at scale.

  • Optimize Google Cloud Platform services usage for performance, cost-efficiency, and security.

  • Monitor system health and troubleshoot performance issues in AI/ML deployments.

  • Ensure compliance with security, governance, and reliability standards in cloud environments.

Required Skills & Experience:

  • 5+ years in Cloud/DevOps engineering, with at least 3 years on Google Cloud Platform.

  • Hands-on experience with Vertex AI, AI/ML pipeline orchestration, and model deployment.

  • Strong knowledge of Google Cloud Platform services: GKE, Cloud Run, BigQuery, Cloud Storage, Pub/Sub, AI Platform, etc.

  • Proficiency in Terraform, Ansible, or equivalent IaC tools.

  • Experience with CI/CD tools (Cloud Build, Jenkins, GitLab CI, etc.).

  • Familiarity with Docker, Kubernetes, and container orchestration in Google Cloud Platform.

  • Knowledge of Python, Bash, or Go for automation scripts.

  • Strong understanding of networking, security, and IAM in Google Cloud Platform.

Nice-to-Have:

  • Experience with Kubeflow, MLflow, or TFX.

  • Understanding of data engineering workflows in Google Cloud Platform.

  • Google Cloud Platform Professional Cloud DevOps Engineer or Professional Machine Learning Engineer certification.

Education:

  • Bachelor s or Master s degree in Computer Science, Engineering, or related field.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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