Machine Learning Engineer

Company Description Tyde Code builds consumer-facing applications and shared payment infrastructure that enable seamless, secure, and efficient financial transactions. The company focuses on creating intuitive digital experiences that make payments simpler and more accessible for a wide range of users. Team members work with modern technologies to design and scale systems that support reliable transaction processing.

Joining Tyde

Code means contributing to products at the intersection of consumer apps and financial technology, with opportunities to solve complex technical and data challenges.

Role Description As a Machine Learning Engineer at Tyde Code, you will design, implement, and optimize models that support consumer apps and payment infrastructure, with a focus on reliability, fraud detection, and user experience. You will work on collecting, cleaning, and transforming large datasets, building and training neural networks and other ML models, and evaluating their performance using statistical methods. Day-to-day tasks include collaborating with software engineers and product teams, integrating ML solutions into production systems, improving algorithms for pattern recognition, and monitoring model performance in real-world environments.

This is requiring close collaboration with local team members and active participation in technical discussions, code reviews, and iterative experimentation.

Qualifications

• Strong foundation in Computer Science and Algorithms, with experience designing efficient, scalable solutions.
• Proficiency in Pattern Recognition and Neural Networks, including building, training, and deploying models in production.
• Solid understanding of Statistics, experimental design, and model evaluation techniques.
• Hands-on experience with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn) and at least one programming language such as Python or Java.
• Experience working with large datasets, data pipelines, and SQL or NoSQL databases.
• Ability to collaborate in cross-functional teams, communicate complex technical concepts clearly, and document work thoroughly.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
• Experience in fintech, payments, or consumer-facing applications is a plus.