Senior Lead Machine Learning Engineer
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About The Position
As a Senior Lead Machine Learning Engineer at Capital One, you will be an integral part of an Agile team focused on the productionization of machine learning applications and systems at scale. Your role will involve detailed technical design, development, and implementation of machine learning applications utilizing both existing and emerging technology platforms. You will concentrate on machine learning architectural design, develop and review model and application code, and ensure the high availability and performance of our machine learning applications. This position offers a unique opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. In this role, you will engage in various ML engineering activities that overlap with disciplines such as Ops, Modeling, and Data Engineering. You will be responsible for designing, building, and delivering ML models and components that address real-world business challenges, collaborating closely with Product and Data Science teams. Your decisions regarding ML infrastructure will be informed by your understanding of ML modeling techniques, including model choice, data and feature selection, model training, hyperparameter tuning, and validation. You will tackle complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment processes. As part of a cross-functional Agile team, you will create and enhance software that supports state-of-the-art big data and ML applications. Your responsibilities will also include retraining, maintaining, and monitoring models in production, leveraging or building cloud-based architectures to deliver optimized ML models at scale, and constructing optimized data pipelines to feed ML models. You will apply continuous integration and continuous deployment best practices to ensure successful deployment of ML models and application code, while ensuring that all code is well-managed to minimize vulnerabilities and that models adhere to best practices in Responsible and Explainable AI. Proficiency in programming languages such as Python, Scala, or Java is essential for this role.
