Senior MLE - MLOps, Python, GCP, VertexAI, GKE

About the role

UPS is looking for a highly skilled MLOps Engineer to design, deploy and manage machine learning pipelines in Google Cloud Platform (GCP). The role covers automating ML workflows, optimizing model deployment, ensuring model reliability and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery and Terraform to build scalable, cost-efficient ML infrastructure, and interact with architects and business stakeholders.

Key responsibilities

• Manage the deployment and maintenance of machine learning models in production, integrating them with existing systems
• Monitor model performance (accuracy, precision, recall, F1 score) and address performance degradation, drift or bias
• Troubleshoot issues, maintain documentation and manage model versions for audit and rollback
• Analyze monitoring data to spot potential issues early and report performance regularly to stakeholders
• Optimize queries and pipelines, and modernize applications when needed

Required profile

• Bachelor's degree in a quantitative field (mathematics, computer science, physics, economics, engineering, statistics, operations research, quantitative social science) or equivalent experience
• Good understanding of ML algorithms, including regression, clustering, neural networks and deep learning
• Strong oral and written communication, and ability to write detailed technical documentation
• Ownership and collaboration, with initiative to improve processes

Required skills

• Python and SQL
• GCP tools: BigQueryML, Vertex AI Pipelines (Kubeflow Pipelines), Model Versioning & Registry, Cloud Monitoring, Kubernetes (GKE)
• MLOps practices, model monitoring and evaluation metrics
• Bonus: Azure MLOps, Cloud Billing, NLP / Gen AI / LLM applications, Agile and Lean Agile