Data & Analytics Specialist - MLOps Engineer

Job summary

The Mid-Level Data MLOps Engineer role is responsible for operationalizing, scaling, and maintaining machine learning models in production. Key responsibilities include designing automated ML pipelines with Vertex AI and Apache Airflow, managing model deployment processes, and provisioning secure GCP environments using Terraform, while ensuring code quality and implementing monitoring systems for model performance.

Qualifications

• 3 to 5 years of production experience in an MLOps, DevOps, or Machine Learning Engineering role
• Professional-level proficiency in Python
• Professional experience implementing Vertex AI ML Pipelines
• Practical experience querying BigQuery
• Solid experience configuring pipeline scripts in Jenkins
• Hands-on experience writing and maintaining infrastructure modules using Terraform
• Direct experience establishing mandatory unit testing frameworks

Responsibilities

• Design, orchestrate, and maintain automated machine learning pipelines using Vertex AI ML Pipelines and Apache Airflow
• Own the model deployment process, including data pre-processing, performance optimisation, model serialisation, and automated continuous training
• Provision and manage secure, reproducible GCP environments and ML infrastructure modules using Terraform
• Build and optimize automated deployment pipelines using Jenkins, managing containerisation workflows with Docker
• Enforce software engineering best practices within the data science lifecycle
• Interface with core retail data warehouse, optimizing data retrieval from BigQuery
• Implement monitoring systems for model drift, data drift, and inference latency

Skills

Certifications

Relocation