Machine Learning Engineer - APAC
Malaysia-LN Kuala Lumpur
USD 82K-158K (estimate) Mid-level Full Time
Tasks
- Assess feature importance and stability
- Automate data processing and deployment pipelines
- Clean transform join datasets
- Conduct A B rollouts
- Conduct model experiments
- Create agentic workflows for intelligent solutions
- Create features with aggregation encoding interaction time windows
- Deploy models on Databricks
- Design and develop machine learning models
- Document methodologies, assumptions, and results
- Evaluate models with statistical metrics
- Handle missing data outliers normalization
- Implement monitoring for drift and performance
- Manage class imbalance
- Optimize hyperparameters
- Prevent data leakage
- Reduce variance and bias
- Tune regularize and ensemble models
- Use cross validation
- Use train validation test splits
Perks/Benefits
- Family benefits
- Flexible working arrangements
- Learning and development resources
- Sabbaticals
- Study assistance
Skills/Tech-stack
A/B | A/B Testing | B testing | CI/CD | Calibration | Classification | Confusion matrix | Cross-validation | Data Leakage Prevention | Data leakage | Data pipeline | Data pipeline orchestration | Databricks | ETL | Ensembling | F1-score | Feature Engineering | Generative AI | Hyperparameter Tuning | Hypothesis Testing | Leakage prevention | MLflow | Machine Learning | Microsoft Fabric | Model Monitoring | NLP | Pipeline Orchestration | Power BI | PowerApps | Precisión | Python | ROC-AUC | Recall | Regression | Regularization | SQL | Series analysis | Time Series | Time Series Analysis | Version control | Workflow automation
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Language: en
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