Job Description Senior Manager, Machine Learning Engineering As a Capital One Senior Manager of Machine Learning Engineering, you'll manage an Agile teamdedicated to developing, optimizing, delivering, and improving machine learning applications andsystems.Youll participate in the detailed technical design, development, and implementation ofmachine learning applications using existing and emerging technology platforms. Working withinan Agile environment, youll serve as a technical lead, guiding machine learning architecturaldesign decisions, developing and reviewing model and application code, and ensuring highavailability and performance of our machine learning applications. You'll have the opportunity tocontinuously learn and apply the latest innovations and best practices in machine learningengineering. Youll mentor other engineers and develop your technical knowledge and skills tokeep Capital One at the cutting edge of technology. What youll do in the role: Manage a team of engineers with deep experience in machine learning and distributed systems Lead a portfolio of diverse machine learning projects Deliver ML software models and components that solve real-world business problems, while working in collaboration with our 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 atscale Construct optimized data pipelines to feed ML models Use programming languages like Python, Scala, or Java Leverage Continuous Integration and continuous deployment best practices, includingtest automation and monitoring, to ensure successful deployments of ML models andapplication code Advocate for software and machine learning engineering best practices Function as the engineering tech lead for large-scale initiatives Attract, recruit, and support diverse ML engineering talent Mentor junior ML engineering talent Basic Qualifications Bachelors degree At least 8 years of experience designing and building data-intensive solutions using distributed computing 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 At least 4 years of people management experience. Preferred Qualifications Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 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 Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 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 ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization for thisposition.by Jobble