Senior Machine Learning Engineer

About Prezzee Prezzee is a global leader in digital gifting and payments, having sold over 140 million gift cards through partnerships with more than 1,500 brands and serving over 6 million customers worldwide. Our mission is to change lives through the power of giving — leveraging borderless payment technology and innovative digital solutions to help people connect and create memorable moments that truly matter. The Role:Are you ready to transform customer experience and lead the charge in fraud detection? As a Senior Machine Learning Engineer, you’ll play a pivotal role in shaping the future of our AI/ML capabilities. Collaborating with teams across Fraud, Technology, Product, Sales, and Finance, you'll design, train, and deploy advanced machine learning models to enhance customer experience and protect against fraud. Your work will directly drive business growth while ensuring robust fraud prevention.   What You'll Be Doing: Design & Innovate: Create and refine machine learning algorithms that enhance customer experience (CX) and fight fraud, pushing the boundaries of what’s possible. Optimise Performance: Experiment with new techniques, architectures, and feature selection to ensure top-tier model performance. Clean and Curate Data: Work with large datasets, ensuring high-quality data for training and testing – setting the stage for powerful, reliable models. Deploy & Scale: Deploy and maintain machine learning models in production environments, ensuring that they are scalable, efficient, and reliable. Collaborate Cross-Functionally: Collaborate closely with fraud analysts, software engineers, product managers, and business stakeholders to ensure our ML solutions align with the company’s goals, particularly as it relates to fraud detection and prevention. Stay at the Forefront of Innovation: Always be learning and experimenting with emerging trends in machine learning and AI to keep us ahead of the curve.   What We’re Looking For: Core Skills: A strong background in probability, statistics, and algorithms and how to apply these to Fraud Detection and Prevention.  Expertise in machine learning frameworks (e.g., Keras, PyTorch). Experience in deploying machine learning models on cloud platforms such as AWS, GCP, or Azure. Knowledge of scalable machine learning systems and real-time model deployment. Familiarity with data structures, data modeling, and software architecture. Experience with fraud detection techniques, including anomaly detection and graph-based analytics. A solid understanding of MLOps and CI/CD pipelines for ML models.   Why Join Us? You’ll play a key role in shaping the future of digital gifting at a global scale — working with talented people, modern technology, and a culture that genuinely values openness, excellence, and impact. We Offer: Prezzeeversary Leave – Extra day of annual leave for each year you’re with us. BirthYay Leave – Celebrate you with a paid day off during your birthday month....