Principal Machine Learning Engineer

Overview

Lead the execution layer of machine learning, turning research and model capabilities into reliable, scalable production systems. The role spans data, training, evaluation, inference, deployment, and hands-on technical leadership.

What you'll do

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

What you'll need

• Experience building and shipping production ML systems.
• Strong knowledge 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.
• Production-grade coding skills with a focus on correctness and reliability.
• Experience with Python, PyTorch or JAX, and GPU-based training and inference systems.

Details

• Location: China
• Interviews may be virtual and/or onsite.