PPRO
FinTech
SeniorMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Machine Learning Engineer at PPRO. Skills: Machine Learning, MLOps, Real-time systems. Build machine learning models. Train machine learning models”
What You'll Achieve.
Maximize transaction approval rates; Minimize false declines; Process millions of transactions
Industry & Context.
What They're Looking For.
Must Have
5+ years ML experience, Python mastery, SQL proficiency
Nice to Have
Payments domain knowledge, PhD preferred, Cloud platform certifications
What You'll Do.
Build machine learning models
Train machine learning models
Deploy machine learning models
Design inference pipelines
Maintain inference pipelines
Automate model training
Automate model deployment
Drive shadow deployment
Monitor model metrics
Detect model degradation
How You'll Work.
Team & Collaboration
Partner with Product Managers; Partner with Data Analysts; Partner with Core Payments Engineers
Full Job Description
## Description At PPRO, our mission is to simplify access to local payment methods and our vision is to enable the sale of goods and services to anyone in the world using their preferred way to pay. We empower partners such as Ant Group, PayPal and Stripe to access new markets, connect with more customers, and accelerate their growth. Our strength lies in our diverse global team with 50+ nationalities and 10+ international locations- all united around one goal – to deliver the best possible products and services to our partners and customers. While our company mission is to keep innovating global commerce, our internal mission is to #chooseaction, #beopen, #thinkcustomer, #gofurther and #wintogether The Purpose: As a Machine Learning Engineer in PPRO’s Performance Powerhouse team, you will take ownership of building and deploying intelligent systems designed to maximize transaction approval rates and minimize false declines. You will partner with Product Managers, Data Analysts, and Core Payments Engineers to develop real-time predictive models that dynamically route transactions, optimize retry strategies, and adapt to issuer behaviors across the globe. This role is designed for experienced ML practitioners who can seamlessly bridge the gap between data science and software engineering. It provides the opportunity to directly impact the company's bottom line by ensuring millions of legitimate transactions are successfully processed, while also offering the flexibility to grow into technical leadership or specialized ML architecture roles. ## What You Will Be Doing Develop and Deploy ML Models: Build, train, and deploy robust machine learning models focused on card authorization optimization, dynamic routing, and intelligent retries. Real-Time Inference Engineering: Design and maintain low-latency inference pipelines capable of scoring live payment transactions within strict millisecond SLAs. Feature Engineering & MLOps: Collaborate with data teams to build scal
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