Staff/Principal Machine Learning Engineer

What you'll do

• Build reusable ML platform capabilities, including embedding, feature engineering, continuous-learning, and scalable training systems.
• Improve and automate the end-to-end model lifecycle, from data preparation and training through evaluation, serving, and monitoring.
• Define the ML Platform roadmap and guide technical direction in collaboration with research, data, engineering, and product teams.

What they ask for

• Strong theoretical and practical foundation in machine learning and statistics, including model assumptions, bias, uncertainty, evaluation, and failure modes.
• 5-7+ years of hands-on applied machine learning experience, with exposure to production-scale modeling.
• Experience in high-scale ML-driven product environments, especially fintech, pricing, or risk modeling.
• Proficiency in Python and core ML frameworks; demonstrated end-to-end model development expertise.

Nice to have

• Practical experience optimizing ML workflows with CUDA/GPU acceleration.
• Background in feature store design, embedding architecture, or synthetic data generation.

Pay

$220,700 — $300,000 USD (base salary)

Tools

Python, PyTorch, TensorFlow, Scikit-learn, XGBoost, CUDA

AI focus

Build and scale ML infrastructure and automated workflows for model development, training, deployment, evaluation, and monitoring, with the goal of improving predictive accuracy.