Lead Engineer, Machine Learning

Overview

Lead the execution layer of the company’s machine learning intelligence, turning research and model capabilities into reliable, scalable production systems.

What you'll do

• Own end-to-end ML systems from data and training through evaluation, inference, and deployment.
• Build and evolve training and fine-tuning pipelines for large models.
• Design evaluation systems to measure capability, robustness, safety, and product performance.
• Architect high-performance inference systems to optimize latency, GPU utilization, memory, cost, and reliability.
• Build data pipelines for real-world and synthetic training data.
• Establish production infrastructure for deploying, monitoring, and continuously improving models.

What you'll need

• Experience building and shipping production ML systems (not only research prototypes).
• Understanding of large-model training, fine-tuning, evaluation, and inference.
• Strong software engineering and systems fundamentals.
• Experience operating ML workloads at meaningful scale, especially GPU-based systems.
• Technical judgment to navigate ambiguous problems independently.
• Bias toward experimentation, measurement, and shipping.

Details

• Location: Singapore.