Senior Machine Learning Engineer (Risk Modelling)
Type: Full-time
Location- Remote
Experience- 5+ years
About the role
We are hiring a Senior Machine Learning Engineer to lead the modelling workstream of a large-scale predictive analytics programme. You will build and productionise a risk-based classification system that scores spare-parts criticality across an enterprise asset base, turning maintenance, inventory, and supply chain data into a deployed decision-support engine. This is a hands-on delivery role in a fixed-timeline engagement, from feature design through production deployment and handover.
What you'll do
- Design and engineer features from enterprise maintenance, inventory, and planning data (equipment master, failure history, BOM structures, lead times, demand variability, supplier and obsolescence risk)
- Develop, validate, and deploy an ML vulnerability scoring model on Databricks, with rigorous cross-validation, hyperparameter tuning, and baseline benchmarking against a defined AUC acceptance target
- Build the risk classification engine assigning composite scores and A/B/C criticality classes, with configurable thresholds and documented recalibration governance
- Implement MLOps practices: experiment tracking in MLflow, CI/CD-based deployment, drift detection, performance alerting, and executable retraining procedures
- Co-design scoring parameters with supply chain and plant maintenance stakeholders; present model design and results to technical and business audiences
- Support SIT/UAT, resolve model-related defects, and deliver technical documentation and knowledge transfer
What you'll need
- 5+ years of hands-on ML engineering experience, with demonstrable delivery of risk modelling, classification, or scoring systems into production
- Strong Python and Spark; production experience on Databricks (Delta Lake, MLflow, Workflows)
- Solid grounding in classification model evaluation (AUC/ROC, calibration, handling class imbalance) and feature engineering on messy enterprise data
- Experience deploying and operating models via CI/CD with drift monitoring and retraining
- Clear communication skills; comfortable presenting model decisions to non-technical stakeholders
- Immediate or short-notice availability preferred
Nice to have
- Databricks Certified ML Associate or Professional (certification support provided)
- Domain experience in asset-intensive industries: plant maintenance, spare parts, supply chain, or reliability engineering (RCM/IEC 60300 awareness a plus)
- Familiarity with SAP PM/MM data structures
- Prior delivery experience in the GCC region
Interested candidates share their resume at [Confidential Information]
