Machine Learning Engineer
Core
Deploy and monitor machine learning models in production environments, manage cloud infrastructure, and build data pipelines for EY's Technology Consulting practice.
Role type
Machine Learning Engineer (MLOps focus)
Builds
Production ML models, data pipelines, and monitoring infrastructure for client engagements
Domain
Professional Services / Consulting / Data Engineering
Deliverable
production ML models
Required skills
Model integration and deployment, Cloud resource management, CI/CD pipeline implementation, Data pipeline construction, Model performance monitoring, Data security compliance
Preferred skills
DevOps practices, Containerization (Docker, Kubernetes), MLOps tools (MLflow, Kubeflow, SageMaker), Infrastructure provisioning
Technologies
AWS, Azure, GCP, Cloudera, Docker, Kubernetes, MLflow, Kubeflow, Synapse Analytics, SageMaker
Responsibilities
Collaborate with data scientists on model integration, Set up infrastructure for model deployment, Manage and optimize cloud resources, Implement CI/CD pipelines, Build and maintain data pipelines, Monitor model performance and system health, Ensure data security and compliance
Seniority
Mid-level, hands-on IC
