AI ML Engineer MLOps - UPS Digital MarTech

Role Overview UPS is hiring a Senior ML Engineer with a focus on MLOps to join its Machine Learning Engineering team at the Global Customer Platform. This role is central to operationalizing marketing ML models and bridging the gap between experimental data science and production-grade engineering. You will work within the Digital MarTech ecosystem to deploy, automate, monitor, and scale intelligent systems that power personalization, retention, and revenue growth initiatives across UPS's global customer base. Key Responsibilities - Deploy production-ready marketing ML models including Propensity to Buy, Churn Prediction, and Customer Lifetime Value models into the Global Customer Platform - Build and maintain fully automated training, retraining, and inference pipelines with CI/CD integration for the complete ML lifecycle - Enable low-latency real-time decisioning and scalable batch scoring workflows while eliminating manual scoring processes - Design and manage feature store infrastructure to ensure consistency between training and inference environments - Monitor model performance in production, detect data drift and concept drift, and track prediction accuracy, stability, and bias metrics - Maintain model versioning, reproducibility standards, and governance compliance across all deployed systems - Collaborate with data science, software engineering, and product teams to align ML solutions with UPS strategic goals - Mentor junior engineers and help shape MLOps best practices across the team Required Qualifications - 5 to 10 or more years of experience in ML engineering, data engineering, or MLOps roles - Strong hands-on experience deploying ML models into production environments at scale - Proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, and PyTorch - Experience with orchestration tools such as Airflow, Kubeflow, or equivalent platforms - Familiarity with containerization and deployment technologies including Docker and Kubernetes - Working knowledge of cloud platforms such as Azure, AWS, or GCP - Solid understanding of feature stores, model lifecycle management, and drift detection tooling - Preferred experience in marketing analytics, customer data platforms, CDP integrations, and real-time personalization systems - Understanding of customer segmentation, campaign activation workflows, and ML governance standards Why Join Us UPS is one of the Fortune 500's most recognised global organisations, and its ML Engineering teams build scalable intelligent systems that move up to 38 million packages every day. Joining this team means working on high-impact production AI solutions alongside talented professionals in a culture that champions innovation, inclusion, and continuous growth.

- 5 to 10 plus years in ML engineering, data engineering, or MLOps - Proficiency in Python and frameworks like Scikit-learn, XGBoost, TensorFlow, PyTorch - Experience with Airflow, Kubeflow, or similar orchestration tools - Hands-on knowledge of Docker and Kubernetes for containerisation and deployment - Experience with cloud platforms such as Azure, AWS, or GCP - Strong understanding of feature stores and model lifecycle management - Knowledge of model monitoring and drift detection tools - Experience with CI/CD pipelines for ML lifecycle management - Preferred experience in marketing analytics or customer data platforms

- Opportunity to work with a Fortune 500 global organisation - Work on large-scale production ML systems impacting billions of shipments - Collaborative and inclusive work environment - Career growth and mentorship opportunities - Full-time permanent employment