Machine Learning Engineer, Sardine

• Hands-on experience with applied ML using large datasets (PyTorch, Scikit-learn, etc.)
• Strong SQL skills and familiarity with relational and non-relational databases
• Experience with end-to-end ML systems: feature pipelines, model deployment, monitoring, and iteration
• Excellent communication skills in English, both written and verbal
• Bachelor's or Master's in Computer Science, Engineering, or a related discipline

Desirable

• As a Machine Learning Engineer, you’ll do more than build models - you’ll design the systems that make fraud detection possible. You’ll work across modeling, data pipelines, and backend systems (Go) to ensure ML models run reliably, efficiently, and at scale
• This is a chance to combine applied ML with large-scale systems engineering, owning end-to-end solutions that tackle high-stakes, ever-evolving challenges
• Build and optimize data pipelines and backend services to process device and behavioral data in real time
• Develop and deploy ML models for fraud detection, ensuring they run reliably and efficiently in production
• Turn raw data into production-ready features that feed our fraud detection systems
• Collaborate with platform and backend engineers to integrate models seamlessly
• Maintain high standards of security, privacy, and compliance
• Champion best practices in testing, documentation, and observability