Machine Learning Engineer, AVP

Role Overview: Join us as a Machine Learning Engineer. Deploy, automate, maintain, and monitor machine learning models and algorithms in a production environment. Collaborate with colleagues to design and develop state-of-the-art machine learning products. This role is offered at the associate vice president level, providing you with the opportunity to turn your interests into a diverse and rewarding career in a non-stop innovation environment. Key Responsibilities: - Lead the planning and design of complex projects - Codify and automate machine learning model production - Deploy and maintain end-to-end solutions - Build metrics to improve system performance - Identify and resolve differences in data distribution affecting model performance - Understand business stakeholder needs and align machine learning solutions to support business strategy - Produce machine learning models, including pipeline designs, development, testing, and deployment - Create frameworks for robust monitoring of machine learning models in the production environment - Deliver high-quality models and address performance shortfalls through retraining - Work in an Agile manner within multi-disciplinary data and analytics teams to achieve project outcomes Qualifications Required: - Academic background in a STEM discipline such as Mathematics, Physics, Engineering, or Computer Science - Experience in machine learning on large datasets and understanding of machine learning approaches and algorithms - Experience in building, testing, supporting, and deploying machine learning models using CI/CD tools like TeamCity and CodeDeploy - Good communication skills to engage with stakeholders - Experience coaching others - Knowledge of data science and machine learning - Proficiency in Python programming with hands-on experience in traditional ML, GenAI, and Agentic AI applications - Conducting demos of AI tooling and contributing to automation initiatives in responsible AI space - Knowledge of financial services and the ability to identify wider business impacts, risks, and opportunities (Note: Additional details of the company were not included in the provided job description.) Role Overview: Join us as a Machine Learning Engineer. Deploy, automate, maintain, and monitor machine learning models and algorithms in a production environment. Collaborate with colleagues to design and develop state-of-the-art machine learning products. This role is offered at the associate vice president level, providing you with the opportunity to turn your interests into a diverse and rewarding career in a non-stop innovation environment. Key Responsibilities: - Lead the planning and design of complex projects - Codify and automate machine learning model production - Deploy and maintain end-to-end solutions - Build metrics to improve system performance - Identify and resolve differences in data distribution affecting model performance - Understand business stakeholder needs and align machine learning solutions to support business strategy - Produce machine learning models, including pipeline designs, development, testing, and deployment - Create frameworks for robust monitoring of machine learning models in the production environment - Deliver high-quality models and address performance shortfalls through retraining - Work in an Agile manner within multi-disciplinary data and analytics teams to achieve project outcomes Qualifications Required: - Academic background in a STEM discipline such as Mathematics, Physics, Engineering, or Computer Science - Experience in machine learning on large datasets and understanding of machine learning approaches and algorithms - Experience in building, testing, supporting, and deploying machine learning models using CI/CD tools like TeamCity and CodeDeploy - Good communication skills to engage with stakeholders - Experience coaching others - Knowledge of data science and machine learning - Proficiency in Python programming with hands-on experience in traditional ML, GenAI, and Agentic AI applications - Conducting demos of AI tooling and contributing to automation initiatives in responsible AI space - Knowledge of financial services and the ability to identify wider business impacts, risks, and opportunities (Note: Additional details of the company were not included in the provided job description.)