Capital One
Senior Lead Machine Learning Engineer
Capital One, Richmond, Virginia, United States, 23214
Center 3 (19075), United States of America, McLean, VirginiaSenior Lead Machine Learning Engineer
As a Capital One
Machine Learning Engineer (MLE),
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. 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.What you'll do in the role:
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.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 vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.Use programming languages like Python, Scala, or Java.About the Team
In the Enterprise Data Tech Organization customer experience is at the forefront of what we do. This team builds functional, always-on scalable data ecosystems working alongside some of the savviest Data techies in the industry, enabling products and solutions to enhance customer experience and drive up satisfaction levels. In addition, the team manages/builds data solutions, solving customer reported problems, identifying and solving production issues, and implementing integrated solutions that meet our customers' needs.Basic Qualifications:
Bachelor's degreeAt 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 JavaAt least 3 years of experience building, scaling, and optimizing ML systemsAt least 2 years of experience leading teams developing ML solutionsPreferred Qualifications:
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar fieldExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow3+ years of experience developing performant, resilient, and maintainable code3+ years of experience with data gathering and preparation for ML models3+ years of people management experienceML industry impact through conference presentations, papers, blog posts, open source contributions, or patents3+ years of experience building production-ready data pipelines that feed ML modelsAbility to communicate complex technical concepts clearly to a variety of audiencesCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days. No agencies please.
Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.
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As a Capital One
Machine Learning Engineer (MLE),
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. 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.What you'll do in the role:
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.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 vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.Use programming languages like Python, Scala, or Java.About the Team
In the Enterprise Data Tech Organization customer experience is at the forefront of what we do. This team builds functional, always-on scalable data ecosystems working alongside some of the savviest Data techies in the industry, enabling products and solutions to enhance customer experience and drive up satisfaction levels. In addition, the team manages/builds data solutions, solving customer reported problems, identifying and solving production issues, and implementing integrated solutions that meet our customers' needs.Basic Qualifications:
Bachelor's degreeAt 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 JavaAt least 3 years of experience building, scaling, and optimizing ML systemsAt least 2 years of experience leading teams developing ML solutionsPreferred Qualifications:
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar fieldExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow3+ years of experience developing performant, resilient, and maintainable code3+ years of experience with data gathering and preparation for ML models3+ years of people management experienceML industry impact through conference presentations, papers, blog posts, open source contributions, or patents3+ years of experience building production-ready data pipelines that feed ML modelsAbility to communicate complex technical concepts clearly to a variety of audiencesCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days. No agencies please.
Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.
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