Principal Machine Learning Engineer

We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform, designing and building end-to-end infrastructure for training, evaluation, and productionization of ML models, and influencing foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines.

Requirements

• Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models
• Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines
• Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading
• Work with researchers to adapt and deploy modern architectures — transformers, state-space models, temporal convolutions, graph neural networks — to noisy, high-frequency financial data
• Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment
• Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work
• Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work — whether that's new architectures, training techniques, or tooling

Benefits

• Paid leave
• Insurance