Staff Machine Learning Engineer

Location

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Remote

Employment Type

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Full time

Location Type

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Remote

Department

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Engineering

Payabli

is a next-generation Payments Infrastructure and Monetization Platform purpose-built for vertical software companies. Through a single, developer-friendly API with low-code embedded payment components, Payabli enables platforms to seamlessly embed, monetize, and operationalize payments—making payments a core part of their platform and business model.

By unifying payment acceptance, payment issuance, and advanced payment operations tooling, Payabli empowers software companies to manage and move money through a single infrastructure stack that delivers total control over the payments experience. Built to scale with PCI DSS 4.0 and SOC 2-compliant security, Payabli’s infrastructure delivers enterprise-grade reliability and trust while leveraging AI-driven intelligence to enhance visibility, streamline operations, and drive revenue growth.

Backed by leading fintech investors including QED Investors, Fika Ventures, TTV Capital, and Bling Capital, Payabli is setting the standard for embedded payments infrastructure powering the next generation of vertical SaaS.

About the Role

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Payabli is looking for a Staff Machine Learning Engineer to set the technical direction for ML at Payabli. A few models are already live and driving real decisions: reducing time-to-clear for risk reviews and scoring transactions and merchants. But that's the starting line, not the destination. We want to build a broad portfolio of models that make payments smarter and easier: automatically choosing the best payment method, reducing disputes and chargebacks, improving authorization rates, forecasting payouts, and more. We need a technical anchor who can both raise the bar on what's live today and stand up many new models from scratch, owning evaluat