Principal Machine Learning Engineer
Core
Define ML architecture and drive MLOps maturity for a new matching platform powering financial market services.
Role type
Principal Machine Learning Engineer (SageMaker, MLOps, Model Governance)
Builds
Scalable, secure, and explainable ML systems for a matching platform
Domain
Financial markets infrastructure
Deliverable
production ML models
Required skills
AWS SageMaker, MLOps, PyTorch, TensorFlow, XGBoost, SHAP, data lakehouse architecture, model governance, CI/CD, infrastructure-as-code
Preferred skills
None stated
Technologies
AWS SageMaker, PyTorch, TensorFlow, XGBoost, SHAP
Responsibilities
Define end-to-end ML architecture including data pipelines and inference runtimes; Lead adoption of MLOps patterns and platform tooling; Architect scalable feature pipelines within Lakehouse environments; Lead design of ranking, scoring, and similarity models; Establish explainability standards using SHAP for regulator-ready reason codes; Architect automated training, deployment, and retraining pipelines; Design low-latency, high-throughput inference services; Define observability standards for drift detection and monitoring.
Seniority
Principal, hands-on IC with strategic leadership
