Vice President AI Machine Learning Software Engineer I

Designs and creates end-to-end automation of a machine learning pipeline solutions based off specific business and functional requirements of machine learning models. Consults with businesses to identify needs and translates those needs into machine learning solutions. Maintain pipeline functionality and currency (technical debt and gain). Integrate automated lifecycle components into a fully functional pipeline. Apply data and model governance principles. Defines, creates and maintains a meaningful set of metrics. Establishes relationships to obtain data needed for metrics. Identifies and contacts appropriate managers and professionals to gather necessary information to be added to central reporting database. Conducts studies to provide additional facts needed to make informed decisions about organizational and functional effectiveness of machine learning products. Executes full machine learning lifecycle development and deployment. Programming and maintaining well-designed, testable, efficient code; analyze, design, and develop tests, test-automation and maintain artifacts in support of fully functional machine learning pipeline solutions. Develop software pipeline verification plans and quality assurance procedures. Troubleshoot, debug and upgrade existing systems. Implement standards and procedures that ensure optimal functionality of feature factory, model registry, model monitoring and model retraining components. Participate in model deployment process following all change controls. Provide ongoing maintenance, support and enhancements in existing systems and platforms. Provide recommendations for continuous improvement of machine learning pipeline components and MLOps functions. Familiarity with Container Orchestration system, Configuration management tools. Knowledge of modern cloud solution for AI/ML and experience working with highly available and distributed software. Practical familiarity with ML libraries and programming languages. Strong skills in Application user interface (APIs) Implements requirements for model integration with UI for inferencing. Performs analysis of datasets and machine learning models through testing to identify fine tuning opportunities to improve model and pipeline performance. May use machine learning frameworks. Assists team in enforcing model governance. Communicates effectively with technical and business staff. Develops reports and prepares and delivers both informational and decision-seeking presentations. Stays abreast of organization and management changes and has in-depth knowledge of company practices relevant to MLOps and machine learning. Maintains knowledge of companys total computing environment and planned changes in order to develop meaningful machine learning products. Monitors industry and marketplace technology practices and benchmarks related to banking industry and supporting the machine learning strategy. Stays abreast of technology innovations and trends to recommend areas for improvement. Supervises resources by providing instruction, making assignments, directing, and checking the work of applications developers. Provides training in technical tools and skills, as well as specific applications and their business functions to maximize their contribution. Grow and develop skills in: MLOps, big data systems, machine learning concepts, NLP, anomaly detection, generative AI. Contributes to the achievement of related teams objectives. Modified based upon local regulations/requirements. Bachelors degree in STEM engineering degree, or equivalent work experience with experience preferred in related fields. 3-5 years of related experience required; experience in the securities or financial services industry is a plus. BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team-one that is representative and inclusive of the diverse talent, clients and communities we work with and serve-and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.