GCP Data & AI/MLOps Engineer

Job summary

Seeking an experienced GCP Data & MLOps Engineer to design, develop, and deliver modern data, AI/ML, and cloud-native platform solutions.

Qualifications

• Strong hands-on experience with Google Cloud Platform
• Experience developing customised data pipelines using Dataflow and Apache Beam
• Strong Python development skills, including experience building reusable Python libraries
• Experience working with BigQuery for data extraction, preprocessing, and automated scheduling
• Experience building Dataflow Flex Template Frameworks
• Experience delivering AI-based solutions on GCP
• Strong understanding of DevOps and MLOps practices
• Experience applying DevOps methodologies to machine learning systems
• Experience designing and implementing Kubeflow Pipelines
• Experience with GCP Model Registry and model lifecycle management
• Experience developing microservices using REST APIs
• Experience with Python Django application development
• Experience automating Cloud Run and Cloud Functions deployments
• Experience with automated Cloud Build implementations
• Knowledge of Secret Manager, Cloud KMS, and deterministic encryption
• Experience deploying dashboards using R Shiny or Python Django
• Experience developing customised web applications for AI platform resource management
• Strong understanding of cloud-native application development and platform automation
• Strong analytical, troubleshooting, optimisation, and problem-solving skills
• Good communication skills with the ability to work across technical and business teams

Responsibilities

• Design, build, and maintain customised data pipeline frameworks using Google Cloud Platform
• Develop scalable data processing solutions using Dataflow, Apache Beam, Python, and BigQuery
• Build and maintain Dataflow Flex Template Frameworks and domain-specific Python libraries
• Perform BigQuery data extraction, preprocessing, and automated job scheduling
• Design and implement Kubeflow Pipelines for automated ML pipeline creation and deployment
• Deliver AI-based solutions on the GCP platform
• Apply DevOps and MLOps practices across the data and machine learning lifecycle
• Implement automation and monitoring across data flows, ML systems, and cloud services
• Manage model lifecycle, maintenance, and governance using GCP Model Registry
• Enable continuous deployment of Django applications on GCP
• Automate deployment and management of Cloud Run services and Cloud Functions
• Implement automated CI/CD pipelines using Cloud Build
• Develop REST API-based microservices to support platform and application integration
• Implement Secret Manager and Cloud KMS, including deterministic encryption
• Develop customised web applications for AI Platform resource creation and management
• Deploy and maintain dashboards using R Shiny and Python Django
• Optimise application code, data pipelines, and technical deliverables to improve performance and efficiency

Skills

Relocation