Senior Machine Learning Engineer
11 West 19th Street (22008), United States of America, New York, New York Senior Machine Learning Engineer As a Capital One Machine Learning Engineer, you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Working within an Agile environment, you ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering to keep Capital One at the cutting edge of technology. What you ll do in the role: Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. 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, next generation big data and machine learning applications. Leverage cloud-based architectures and technologies to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Use programming languages like Python, Scala, or Java. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Basic Qualifications: Bachelor s degree. At least 1 year of experience designing and building data-intensive solutions using distributed computing. At least 1 year of experience programming with Python, Scala, or Java. At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow). Preferred Qualifications: Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform. Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field. At least 1 year of experience working with large code bases in a team environment. At least 1 year of experience with distributed file systems or multi-node database paradigms. Contributed to open source ML software. At least 1 year of experience building production-ready data pipelines that feed ML models. At this time, Capital One will not sponsor a new applicant for employment authorization for this position.