Machine Learning Engineer

We are seeking an experienced and highly motivated Machine Learning Engineer to join our team and play a key role in designing, developing, and deploying scalable machine learning solutions within a financial services environment. This position is ideal for an individual who is passionate about translating advanced machine learning models from research and prototyping stages into robust, production-ready systems that drive real business impact. The successful candidate will work closely with cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders, to deliver high-quality machine learning solutions that support complex financial use cases. This role requires a strong blend of software engineering expertise, applied machine learning knowledge, and the ability to operate effectively in a fast-paced, regulated industry. Key Responsibilities • Design, develop, and implement end-to-end machine learning solutions, from data ingestion and feature engineering through model training, validation, deployment, and monitoring. • Productionize machine learning models by building scalable, reliable, and maintainable systems that meet performance, security, and compliance requirements. • Develop and maintain infrastructure, pipelines, and tools to support model training, deployment, versioning, and ongoing monitoring in production environments. • Collaborate closely with business and technical stakeholders to understand requirements, translate them into technical solutions, and communicate results effectively. • Analyze large and complex datasets to extract insights, engineer features, and improve model performance. • Ensure model quality through rigorous testing, performance evaluation, and continuous improvement. • Support and enhance machine learning solutions for financial services use cases, particularly within Equity and Fixed Income trading domains. • Contribute to best practices around machine learning engineering, software development standards, and operational excellence. Required Qualifications • Strong programming experience in Python and Java, with exposure to additional languages commonly used in machine learning and data engineering. • Solid understanding of machine learning algorithms, statistical methods, and model evaluation techniques. • Hands-on experience with industry-standard machine learning frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn. • Demonstrated expertise in data analysis, data processing, and feature engineering using structured and unstructured datasets. • Proven experience building and supporting infrastructure for training, deploying, and monitoring machine learning models at scale. • Track record of successfully moving machine learning models from prototype or research environments into production systems. • Strong communication and collaboration skills, with the ability to work independently and partner effectively with a wide range of stakeholders. Preferred Experience • Prior experience within Financial Services, particularly supporting Equity or Fixed Income trading use cases. • Familiarity with building machine learning solutions in regulated or high-availability environments. • Experience working in agile or fast-paced engineering teams.