Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)
Not Disclosed•Full-TimeOn-site
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
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.
As a Capital One Machine Learning Engineer, you will be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. This team focuses on the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms, ensuring high availability and performance.
In this Sr. Lead position, you will bridge the gap between Ops, Modeling, and Data Engineering. You will participate in the architectural design of machine learning systems, developing and reviewing model and application code to solve complex, real-world business problems. Your day-to-day involves collaborating with Product and Data Science teams to inform infrastructure decisions, construct optimized data pipelines, and leverage cloud-based architectures to deliver models at scale.
You will be expected to continuously learn and apply the latest innovations and best practices in machine learning engineering. A key part of your mission is ensuring that all code is well-managed, models are well-governed from a risk perspective, and the ML lifecycle follows best practices in Responsible and Explainable AI. You will also lead teams in retraining, maintaining, and monitoring models in production while utilizing continuous integration and deployment best practices.
Capital One is committed to a fair and efficient recruiting process. We expect this role to accept applications for a minimum of 5 business days. Please note that no agencies are accepted for this position. For technical support or questions about the recruiting process, please contact Careers@capitalone.com.
If you require an accommodation during the application or interview process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to the extent required to provide needed reasonable accommodations.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. We promote a drug-free workplace and consider qualified applicants with a criminal history in a manner consistent with applicable laws.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being. We also consider sponsoring qualified applicants for employment authorization for this position.
Work model: On-site
NYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
New York, New York
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. 3+ years of people management experience. 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.
Skills: Machine Learning, Python, Scala, Java, Aws, Azure, Google Cloud Platform, Scikit-Learn, Pytorch, Dask.
Education: Bachelor's degree required; Master's or doctoral degree in computer science preferred; Doctoral degree in computer science preferred.