GCP Data Engineer

This role is for a "GCP Certified MLOps Data Engineer" on a remote, long-term contract with a competitive pay rate. Key skills include GCP expertise, AWS to GCP migration experience, Terraform, and GitHub Runners proficiency.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
640
🗓️ - Date discovered
January 15, 2025
🕒 - Project duration
More than 6 months
🏝️ - Location type
Remote
📄 - Contract type
Unknown
🔒 - Security clearance
Unknown
📍 - Location detailed
United States
🧠 - Skills detailed
#Infrastructure as Code (IaC) #Cloud #ML (Machine Learning) #Scala #Security #GCP (Google Cloud Platform) #ML Ops (Machine Learning Operations) #GitHub #Compliance #AWS (Amazon Web Services) #Terraform #Monitoring #Scripting #Data Engineering #Bash #Data Science #Grafana #Docker #Prometheus #Kubernetes #Automation #Python #Storage #Deployment #Logging #AI (Artificial Intelligence)
Role description
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Role: GCP Certified MLOPs Data Engineer

We are looking for a savvy GCP Certified MLOps Engineer with exposure to join our growing team of MLOPs/AIOps Team.

Job Description: GCP MLOps Infrastructure Engineer

Role Overview: We are seeking a highly skilled GCP MLOps Infrastructure Engineer to join our team on a long-term contract basis. The ideal candidate will have a strong background in building and maintaining MLOps infrastructure, with experience in helping customers transition from AWS to GCP. Proficiency in GitHub Runners and Terraform is highly desirable.

Key Responsibilities:
• Design, implement, and manage MLOps infrastructure on Google Cloud Platform (GCP).
• Collaborate with data scientists and engineers to streamline the deployment of machine learning models in production environments.
• Assist customers in migrating MLOps workflows from AWS to GCP, ensuring minimal disruption and optimal performance.
• Develop and maintain infrastructure as code using Terraform to manage and provision GCP resources.
• Implement CI/CD pipelines using GitHub Runners to automate the testing, deployment, and monitoring of machine learning models.
• Optimize and scale GCP infrastructure to meet the growing needs of machine learning operations.
• Ensure best practices in security, scalability, and compliance across the MLOps infrastructure.

Qualifications:
• Proven experience as an MLOps Engineer or similar role, with a focus on GCP.
• Experience in migrating infrastructure and workflows from AWS to GCP.
• Strong expertise in Terraform for infrastructure provisioning and management.
• Proficiency with GitHub Runners for CI/CD pipeline automation.
• Solid understanding of GCP services, including AI/ML tools, Compute Engine, Kubernetes Engine, and Cloud Storage.
• Experience with containerization technologies like Docker and orchestration tools such as Kubernetes.
• Strong problem-solving skills and the ability to work independently in a fast-paced, remote environment.
• Excellent communication and collaboration skills.

Preferred Qualifications:
• Experience with other infrastructure automation tools and scripting languages (e.g., Python, Bash).
• Familiarity with monitoring and logging tools (e.g., Stackdriver, Prometheus, Grafana) in GCP environments.
• Certification in Google Cloud (e.g., Professional Data Engineer, Professional Cloud Architect) is a plus.