Principal Machine Learning Engineer – Quantitative Research & Trading Systems - SYD/HK
Core
Design and evolve large-scale machine learning infrastructure to enable researchers and engineers to build, train, deploy, and optimize advanced models for global trading performance.
Role type
Principal Machine Learning Platform Architect
Builds
Large-scale ML infrastructure for training, evaluation, deployment, and monitoring of trading models
Domain
Financial services / Quantitative trading / Deep learning
Deliverable
infrastructure
Required skills
Python, CUDA, C++, PyTorch, TensorFlow, JAX, distributed training, GPU optimization, deep learning architectures (transformers, state-space models, GNNs, temporal convolution networks), self-supervised learning, representation learning, continual learning, cross-sectional modeling
Preferred skills
None stated
Technologies
PyTorch, TensorFlow, JAX, CUDA
Responsibilities
Designing end-to-end ML infrastructure, driving architectural decisions for data/compute/experimentation, collaborating with research and trading teams, implementing scalable deep learning architectures, building observable ML systems, establishing engineering standards, mentoring engineers, evaluating emerging ML research, optimizing distributed training and model serving
Seniority
Principal, hands-on IC with strategy & mentorship