<p><strong>What role you will play in team:</strong> Design, develop, and implement machine learning solutions to improve operational efficiency and risk management within the financial industry.</p><p><strong>What you will do:</strong> Develop and deploy machine learning models to solve complex business problems related to fraud detection, risk assessment, and algorithmic trading.</p><p><strong>Key responsibility:</strong><ul><li>Develop and implement machine learning models using various algorithms.</li><li>Work with large datasets to train and evaluate models.</li><li>Deploy models into production environments using cloud-based infrastructure.</li><li>Monitor model performance and make improvements as needed.</li><li>Collaborate with other engineers and data scientists.</li><li>Stay updated on the latest advancements in machine learning and AI.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Master's degree in Computer Science, Engineering, or a related field.</li><li>2+ years of experience in machine learning engineering.</li><li>Proficiency in Python or Java.</li><li>Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.</li><li>Experience with cloud platforms such as AWS or Azure.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and comprehensive benefits package.</li><li>Opportunities for professional development and career advancement.</li><li>Collaborative and inclusive work environment.</li><li>Contribute to innovation in the financial technology sector.</li></ul></p><p><strong>A Day in the Life:</strong> A typical day might involve developing and testing machine learning models, deploying models to production, monitoring model performance, and collaborating with colleagues to solve complex problems.</p>