Cloud ML Engineer Vertex AI & DevOps Automation

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

Required 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

Nice to Have:

• 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

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