AI/ML Engineer- MLOps - UPS Digital MARTEC

ups

Chennai, India 5 Years Exp Posted 1d ago

Job Description

. Model Deployment & Productionization

  • Deploy ML models into the Global Customer Platform.

  • Ensure low-latency inference for real-time decisioning where required.

  • Enable scalable batch scoring pipelines.

  • Eliminate manual scoring processes through automation.

2. Pipeline Automation

  • Build automated training and retraining workflows.

  • Develop CI/CD pipelines for ML lifecycle management.

  • Ensure consistent data refresh cycles aligned with SLA requirements.

  • Reduce operational handoffs between Data Science and Engineering teams.

3. Model Monitoring & Governance

  • Monitor model performance in production environments.

  • Detect and mitigate model drift (data drift & concept drift).

  • Track prediction accuracy, stability, and bias metrics.

  • Maintain versioning and reproducibility standards.

4. Feature Engineering & Data Infrastructure

  • Design and maintain feature stores.

  • Ensure feature consistency between training and inference environments.

  • Optimize data pipelines for reliability and scalability.

  • Collaborate with data engineering teams on data schema and quality controls.

Required Skills & Experience

  • 5–10+ years in data engineering, ML engineering, or MLOps roles

  • Strong experience deploying ML models into production environments

  • Proficiency in Python and ML frameworks (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch)

  • Experience with orchestration tools (Airflow, Kubeflow, or similar)

  • Familiarity with containerization and deployment (Docker, Kubernetes)

  • Experience with cloud platforms (Azure, AWS, or GCP)

  • Strong understanding of feature stores and model lifecycle management

  • Knowledge of monitoring tools for drift detection and model performance

Preferred Qualifications

  • Experience working in marketing analytics or customer data platforms

  • Familiarity with CDP integrations and real-time personalization systems

  • Understanding of customer segmentation and campaign activation workflows

    • Experience implementing ML governance and compliance standards