Applied Machine Learning Engineer

Job Scope Investigate production issues, track model performance and roll out improvements based on real-world feedback. Create and refine ML models for classification, ranking, retrieval and personalisation. Set up evaluation pipelines, labelled datasets and metrics to measure model quality.

Enhance search relevance and context retrieval using embeddings, hybrid search and re-ranking. Build and maintain pipelines for ML training, inference and deployment. Develop efficient classifiers and optimise for accuracy, precision, latency and cost.

Fine-tune and adapt existing models where sufficient data is available. Design personalisation models that learn from user behaviour while respecting user privacy.

Understanding of model evaluation, experimentation and performance metrics. Strong sense of ownership and problem-solving ability. Hands-on experience building and deploying ML models in production.

Able to balance model quality, latency, cost and reliability. Solid grounding in machine learning and modern neural network architectures. Comfortable writing production-quality code and working with real-world datasets.

Experience in classification, ranking, retrieval, recommendation systems or personalisation. Tech Stack Production ML systems and inference pipelines Python Embeddings, vector search and ranking models PyTorch / JAX We regret that only shortlisted candidates will be notified. GMP Technologies (S) Pte Ltd | EA License: 09C3051 | EA Personnel: Arcus Ang |