Machine Learning Engineer

** - Lead the planning and design of complex projects related to machine learning - Codify and automate machine learning model production, including pipeline optimization, tuning, and fault finding - Transform data science prototypes and apply suitable machine learning algorithms and tools - Deploy and maintain end-to-end solutions, build metrics to enhance system performance, and resolve differences in data distribution affecting model performance - Understand the business stakeholders' needs and how machine learning solutions support the business strategy - Produce machine learning models with colleagues, from pipeline designs to testing and deployment - Create frameworks to ensure robust monitoring of machine learning models in the production environment - Deliver models of expected quality and performance, addressing any shortcomings through retraining - Lead and work in an Agile manner within multi-disciplinary data and analytics teams to achieve project outcomes **

** - Academic background in a STEM discipline such as Mathematics, Physics, Engineering, or Computer Science - Experience with machine learning on large datasets and understanding of machine learning approaches and algorithms - Experience in building, testing, supporting, and deploying machine learning models in a production environment using modern CI/CD tools like TeamCity and CodeDeploy - Good communication skills to engage with various stakeholders - Coaching experience - Knowledge of data science and machine learning - Proficiency in Python programming with hands-on experience in traditional ML and GenAI and Agentic AI applications - Conduct demos of AI tools and contribute to automation initiatives in responsible AI space - Understanding of financial services and the ability to identify broader business impacts, risks, and opportunities across key outputs and processes (Note: The additional details of the company were not provided in the job description.)