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.
- 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 scalable feature stores, ensuring data quality, and automate model training/deployment pipelines (CI/CD for ML).
- Experimentation & Shadow Testing: Drive A/B testing and shadow deployment strategies to safely measure the real-world impact of your models on live traffic and revenue.
- Model Monitoring: Define and monitor key performance metrics to detect data drift, model degradation, and anomalies in production environments.
Classical & Deep Learning Mastery: Deep practical expertise in designing and tuning high-performance classical ML models (e.g. XGBoost, LightGBM, Random Forests) as well as experience with deep learning.
Ability to rigorously evaluate the trade-offs between model complexity and inference latency as well as experience beyond standard accuracy metrics utilising calibration curves, cost-sensitive learning, and precision-recall trade-offs.
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Software Engineering & Python: Software engineering best practices, Python mastery and experience with the standard ML/Data libraries (Scikit-Learn, Pandas, Numpy) with a strong focus on writing scalable, production-ready code.
Real-Time Systems: Proven ability to build, deploy, and optimize ML models that operate under strict latency and high-throughput constraints.
MLOps Proficiency: Experience taking models from notebooks to production environments using tools like MLflow, Docker, Kubernetes, and CI/CD pipelines.
Strong SQL Proficiency: Ability to write complex queries and wrangle large-scale transactional datasets for feature extraction.
Payments Domain Knowledge (Nice to Have): Understanding of the card payment lifecycle, authorization processes, issuer behavior, 3D Secure, and network rules (Visa, Mastercard).
Cloud Infrastructure: Proven experience deploying and managing ML systems on AWS or similar, including expertise in infrastructure as code.
What's in it for you ? :
Hybrid working - We offer a hybrid structure with a 3 days / week on site expectation, so you can strike the balance between office and home working. In addition to our 30-day holiday allowance, we also provide a work from abroad policy, enabling employees to work remotely for up to another 30 days per year
Learning and Development - We offer a €1,000 annual budget to support your professional growth—because investing in your development benefits us all. In addition, we provide leadership cafés, on-the-job training, and other opportunities to help you grow your skills and thrive in your role.
Insurance - Because better safe than sorry - we want our employees to benefit from various insurances including accident insurance, disability insurance, direct insurance (bAV) and travel insurance.
Enhance Family Leave - We understand the importance of family - that's why we offer enhanced family leave to support you during key life moments.
Gym membership - PPRO helps contribute towards the costs of your gym membership, supporting your physical fitness journey while easing the burden on your wallet
Mental Health Platform - We’ve teamed up with a top well-being platform to provide one-on-one therapy, chat therapy, therapist-led courses, guided meditations, and more.
Our office - Located on St.-Martin-Straße, one stop from Ostbahnhof on the 3 and 7 S-lines. The office is situated in a modern and spacious building with fully multimedia-equipped meeting rooms for up to 30 people. The 4th floor features a kitchen and a lunch area, providing a comfortable space for meals and breaks.
Pet-friendly office- Because work is better with your paw-tners by your side
Our Principles:
We get things done: We are courageous; we take ownership, make decisions and get things done.
We act with trust and integrity: We listen first and challenge respectfully. We seek out and leverage diverse perspectives. We welcome and offer honest and open feedback, always assuming positive intent
We put the customer first: We are laser focused on delivering outstanding outcomes for our customers. We put the customer at the heart of what we do.
We make things better: We boldly explore new ideas and have an unwavering commitment to continuous improvement.
We work as a team: We collaborate closely and value team success over individual achievement.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please refer to our Candidate Privacy Policy - https://www.ppro.com/candidate-privacy-policy/
