Senior Manager, Machine Learning Engineer
About the role
Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Responsibilities
- Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
- Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale
- Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation
- Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
- Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
- Retrain, maintain, and monitor models in production
- Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models
- Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
- Ensure all code is well-managed to reduce