Senior ML Engineer - MLOps and Marketing Technology

Role Overview UPS is hiring a Senior Machine Learning Engineer to join its Digital MarTech team in Chennai. This role sits at the intersection of data science and engineering, focused on operationalizing ML models within the marketing technology ecosystem of a Fortune Global 500 organization. You will help power personalization, targeting, and retention strategies that serve millions of customers globally. 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 automated training, retraining, and inference pipelines with CI/CD integration for full ML lifecycle management - Enable real-time and batch scoring workflows while eliminating manual scoring processes through automation - Monitor model performance in production, detect data drift and concept drift, and maintain prediction accuracy and bias tracking - Design and maintain feature stores ensuring consistency between training and inference environments - Optimize data pipelines for reliability, scalability, and SLA compliance in collaboration with data engineering teams - Mentor junior engineers and contribute to shaping MLOps best practices across the organization Required Qualifications - 5 to 10 or more years of experience in data engineering, ML engineering, or MLOps roles - Strong hands-on experience deploying ML models into production environments - Proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch - Experience with orchestration tools like Airflow or Kubeflow - Familiarity with containerization and deployment using Docker and Kubernetes - Experience with cloud platforms including Azure, AWS, or GCP - Strong understanding of feature stores, model versioning, and ML lifecycle management - Knowledge of monitoring tools for drift detection and model performance tracking Why Join Us UPS offers a rewarding culture built on innovation, collaboration, and meaningful impact at scale, with ML systems that move up to 38 million packages a day. If you are driven to solve complex problems and grow your skills in a global enterprise environment, this is your opportunity to make a measurable difference.

- 5 to 10 or more years in ML engineering, data engineering, or MLOps - Proficiency in Python and frameworks like Scikit-learn, XGBoost, TensorFlow, PyTorch - Experience deploying ML models to production at scale - Hands-on experience with Airflow, Kubeflow, or similar orchestration tools - Containerization and deployment skills with Docker and Kubernetes - Cloud platform experience with Azure, AWS, or GCP - Knowledge of feature stores and model lifecycle management - Familiarity with drift detection and model monitoring tools - Preferred: experience in marketing analytics or customer data platforms - Preferred: understanding of customer segmentation and campaign activation workflows

- Permanent full-time employment with a Fortune Global 500 company - Opportunity to work on large-scale AI systems impacting billions of shipments annually - Collaborative and innovative engineering culture - Career growth and mentorship opportunities - Workplace free of discrimination, harassment, and retaliation