Applied Machine Learning Engineer

About the role

A startup building AI-native applications for everyday communication, coordination and collaboration is hiring an Applied Machine Learning Engineer in Singapore. The company's first product is an agent-first mobile communication app, and the engineer builds and improves ML systems that power these applications, from model development through to production deployment.

Key responsibilities

• Build and improve ML models for classification, ranking, retrieval and personalization
• Develop efficient classifiers and optimize accuracy, precision, latency and cost
• Improve search relevance and context retrieval using embeddings, hybrid search and reranking
• Build personalization models that learn from user behavior while respecting privacy
• Develop evaluation pipelines, labeled datasets and metrics to measure model quality
• Fine-tune and adapt existing models where enough data is available
• Maintain ML training, inference and deployment pipelines
• Debug production issues, monitor model performance and ship improvements based on real-world feedback

Required profile

• Strong foundations in machine learning and modern neural architectures
• Hands-on experience building and deploying ML models in production
• Experience in classification, ranking, retrieval, recommendation systems or personalization
• Understanding of model evaluation, experimentation and performance metrics
• Comfortable writing production-quality code and working with real-world datasets
• Able to balance model quality, latency, cost and reliability; strong ownership and problem-solving skills

Required skills

• Python
• PyTorch / JAX
• Embeddings, vector search and ranking models
• Production ML systems and inference pipelines

The interview process involves 3 to 4 virtual and/or onsite interviews, evaluated by the technical team, with a prompt decision.