Principal Machine Learning Engineer

Overview

Own the execution layer of the company’s intelligence as a hands-on Principal Machine Learning Engineer. Turn research and model capabilities into reliable, scalable production systems across the ML lifecycle.

What you'll do

• Own end-to-end ML systems spanning data, training, evaluation, inference, and deployment.
• Build and evolve training and fine-tuning pipelines for large models.
• Design evaluations for capability, robustness, safety, and product performance.
• Architect inference systems optimized for latency, GPU utilization, memory, cost, and reliability.
• Build real-world and synthetic training-data pipelines.
• Establish production infrastructure for model deployment, monitoring, and improvement.
• Partner with research and application engineering to deliver product improvements.

What you'll need

• Experience building and shipping production ML systems.
• Strong understanding of large-model training, fine-tuning, evaluation, and inference.
• Strong software engineering and systems fundamentals.
• Experience operating GPU-based ML workloads at meaningful scale.
• Strong technical judgment and ability to work independently through ambiguity.
• Python and PyTorch or JAX experience.

Details

• Location: Singapore.
• Interviews may be conducted virtually or onsite.