Machine Learning Engineer
About the role
The Machine Learning Engineer designs, deploys, and maintains production machine learning and AI for Motolite manufacturing and operations. The work covers computer vision, anomaly detection, forecasting, and the MLOps around those systems.
What you'll do
- Build end-to-end machine learning pipelines from data preparation and feature engineering through training, deployment, monitoring, and retraining.
- Operationalize predictive, prescriptive, and vision-based systems for manufacturing and operations.
- Deploy models on cloud, on-premise, and containerized platforms.
- Set MLOps practices including versioning, experiment tracking, a model registry, CI/CD, and reproducible deployment.
- Monitor deployed models for drift, latency, and failures, and retrain or fix them.
Requirements
- Degree in Computer Science, Data Science, Statistics, Mathematics, Industrial Engineering, Applied Mathematics, or a related field.
- At least 2 to 4 years in machine learning engineering, AI development, or data science deployment.
- Proficient in Python and frameworks such as scikit-learn, TensorFlow, or PyTorch.
- Familiar with Docker, Git, MLflow, orchestration, and CI/CD for model deployment.
- Computer vision, anomaly detection, or industrial AI experience is an advantage.
About Motolite
Motolite is the Philippine battery brand of Ramcar. This engineer builds production machine learning for the Sta. Maria plant and related operations.
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