Cloud ML Engineer Vertex AI & DevOps Automation
Posted 1 week ago by 1754633226
Negotiable
Outside
Hybrid
USA
Summary: The role of MLOps Engineer focuses on leveraging Google Cloud Platform and Vertex AI to build and maintain scalable machine learning infrastructure. The engineer will automate workflows and facilitate AI/ML deployments in production environments. Collaboration with ML engineers and data scientists is essential for productionizing models and managing their lifecycle. The position requires extensive experience in DevOps/MLOps and cloud ML engineering.
Key Responsibilities:
- Develop, automate, and manage ML pipelines using Vertex AI Pipelines, Kubeflow, and Cloud Composer
- Deploy and monitor models in production using Vertex AI and CI/CD workflows (Cloud Build, GitHub Actions, etc.)
- Work closely with ML engineers and data scientists to productionize models and manage model versioning, retraining, and rollback strategies
- Manage infrastructure-as-code using Terraform, Deployment Manager, or similar tools
- Implement observability and monitoring (logging, metrics, alerts) using Cloud Monitoring, Prometheus, or Grafana
- Ensure security, governance, and compliance of ML workflows within the Google Cloud Platform ecosystem
- Optimize cost, performance, and scalability of ML systems in production
Key Skills:
- 5+ years in DevOps/MLOps or Cloud ML Engineering, with recent Google Cloud Platform production experience
- Strong hands-on experience with Vertex AI, Cloud Functions, BigQuery, and GCS
- Proficiency with tools like TFX, Kubeflow, Docker, and Kubernetes (GKE preferred)
- Expertise in CI/CD, GitOps, and workflow orchestration
- Programming skills in Python (ML workflows) and Bash/Terraform (infra scripting)
- Solid understanding of model lifecycle, pipeline automation, and ML monitoring
- Bachelor's or Master's in Computer Science, Data Engineering, or related field
Salary (Rate): undetermined
City: Atlanta
Country: USA
Working Arrangements: hybrid
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
We are hiring an experienced MLOps Engineer with hands-on expertise in Google Cloud Platform (Google Cloud Platform) and Vertex AI. You ll be responsible for building and maintaining scalable machine learning infrastructure, automating workflows, and enabling robust AI/ML deployments in production environments.
Key Responsibilities:-
Develop, automate, and manage ML pipelines using Vertex AI Pipelines, Kubeflow, and Cloud Composer
-
Deploy and monitor models in production using Vertex AI and CI/CD workflows (Cloud Build, GitHub Actions, etc.)
-
Work closely with ML engineers and data scientists to productionize models and manage model versioning, retraining, and rollback strategies
-
Manage infrastructure-as-code using Terraform, Deployment Manager, or similar tools
-
Implement observability and monitoring (logging, metrics, alerts) using Cloud Monitoring, Prometheus, or Grafana
-
Ensure security, governance, and compliance of ML workflows within the Google Cloud Platform ecosystem
-
Optimize cost, performance, and scalability of ML systems in production
-
5+ years in DevOps/MLOps or Cloud ML Engineering, with recent Google Cloud Platform production experience
-
Strong hands-on experience with Vertex AI, Cloud Functions, BigQuery, and GCS
-
Proficiency with tools like TFX, Kubeflow, Docker, and Kubernetes (GKE preferred)
-
Expertise in CI/CD, GitOps, and workflow orchestration
-
Programming skills in Python (ML workflows) and Bash/Terraform (infra scripting)
-
Solid understanding of model lifecycle, pipeline automation, and ML monitoring
-
Bachelor's or Master's in Computer Science, Data Engineering, or related field
-
Google Cloud Platform Professional Machine Learning Engineer or DevOps Engineer certification
-
Familiarity with LLMs, RAG, or Vertex AI Search & Conversation
-
Experience with multi-region deployments or hybrid cloud setups
-
Exposure to Data Governance and Responsible AI practices