Senior Machine Learning Engineer (Risk Modelling)

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 [HIDDEN TEXT]