Staff/Principal Machine Learning Engineer
Core
Design foundational tools, infrastructure, and workflows to scale ML innovation and accelerate model development across a high-impact technology environment.
Role type
Staff/Principal Machine Learning Engineer (Platform & Infrastructure)
Builds
Scalable ML platforms, training pipelines, feature engineering workflows, and automated continuous-learning systems.
Domain
Fintech, pricing, risk modeling, and high-scale ML-driven product environments.
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, Scikit-learn, XGBoost, CUDA/GPU acceleration, feature store architecture, embedding systems, synthetic data generation, hyperparameter optimization, automated model selection, statistical reasoning, model evaluation, bias and uncertainty analysis, production deployment, cross-functional collaboration, technical leadership.
Preferred skills
Experience improving model accuracy with measurable business outcomes, familiarity with modern experimentation frameworks.
Responsibilities
Lead engineering initiatives to translate ML requirements into scalable infrastructure; design platforms for training, serving, and managing ML representations; streamline feature engineering workflows; develop automated continuous-learning systems; scale training pipelines for larger datasets and sophisticated architectures; improve the complete ML lifecycle from data readiness to production monitoring; explore new algorithms and develop supporting engineering capabilities; define and influence the roadmap for next-generation ML platforms; collaborate with cross-functional teams to deliver end-to-end ML systems; provide technical leadership and influence engineering and scientific direction.
Seniority
Staff/Principal, hands-on IC with technical leadership and cross-team influence.