Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)

the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices.

- The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

- 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.

- 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.

- Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

- 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 vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

- At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)

- At least 4 years of experience programming with Python, Scala, or Java

- At least 3 years of experience building, scaling, and optimizing ML systems

- At least 2 years of experience leading teams developing ML solutions

- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field

- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

- 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

- 3+ years of experience developing performant, resilient, and maintainable code

- 3+ years of experience with data gathering and preparation for ML models

- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

- 3+ years of experience building production-ready data pipelines that feed ML models

- Ability to communicate complex technical concepts clearly to a variety of audiences

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer