You have 5+ years of experience applying machine learning to real production problems, ideally in payments, fintech, fraud, or other high-volume transactional environments.
You think like a research scientist: you start from a problem, decide what data you need, choose the right modeling approach, and define how you will prove it works.
8+ years in software engineering, including 2-3+ years in a people management role leading engineers.
You have significant experience building and shipping backend and/or ML systems at scale, ideally with exposure to fintech, payments, or another regulated, latency-sensitive domain.
Design, train, and fine-tune ML models for payment optimization use cases — including authorization rate improvement, dynamic routing, cost minimization, and fraud signal detection.
Select and apply the right frameworks (PyTorch, TensorFlow, scikit-learn) per model type and latency budget.
