UP
Full time
🤖 AI / ML
AI/ML Engineer – MLOps – UPS Digital MARTEC at UPS
Listed by DevShelfHub
India (IMEA)
Hybrid
Senior · 5–9 yrs
About the Role
UPS is hiring an AI/ML Engineer – MLOps for its Digital MARTEC team to operationalize machine learning models within the marketing technology ecosystem. This role bridges Data Science and Engineering—transforming experimental models into scalable, monitored, and business-ready solutions.
Join a Fortune Global 500 organization where Machine Learning Engineering powers the Smart Logistics Network and Global Customer Platform.
What you'll do
- Deploy ML models into the Global Customer Platform with low-latency inference
- Enable scalable batch scoring pipelines and eliminate manual scoring
- Build automated training and retraining workflows with CI/CD for ML lifecycle management
- Monitor model performance; detect and mitigate data drift and concept drift
- Track prediction accuracy, stability, and bias metrics
- Design and maintain feature stores with consistency between training and inference
- Optimize data pipelines for reliability and scalability
- Collaborate with data engineering on data schema and quality controls
- Ensure consistent data refresh cycles aligned with SLA requirements
What we're looking for
- 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 (Scikit-learn, XGBoost, TensorFlow, PyTorch)
- Experience with orchestration tools (Airflow, Kubeflow, or similar)
Skills & Technologies
Required
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 (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
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- Operationalize marketing ML models including propensity, churn, and CLV on the Global Customer Platform.
- Deploy production-ready marketing ML models (Propensity to Buy, Churn, CLV)
- Build automated training, inference, and CI/CD-enabled ML pipelines
- Design feature store infrastructure for reusable, governed features
- Implement model monitoring and drift detection systems
- Enable real-time or batch scoring workflows for personalization and targeting
- Bridge Data Science and Engineering with automated handoffs
- Work on revenue optimization and retention strategies
- Shape MLOps practices and mentor junior engineers
- Permanent employee position at a Fortune Global 500 company
- Exposure to CDP integrations and real-time personalization systems
About UPS
UPS Machine Learning Engineering teams use expertise in data science, software engineering, and AI to build next-generation intelligent systems. These systems power the Smart Logistics Network, optimize UPS Airlines, and enhance Global Transportation Operations—moving up to 38 million packages a day with measurable enterprise impact.
- Industry
- Technology
- Company Size
- 500+
- Website
- ups.com
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Job Details
- Type
- Full time
- Level
- Senior
- Experience
- 5–9 years
- Location
- India (IMEA)
- Work Mode
- Hybrid
- Category
- AI / ML
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