Capital One National Association
Senior Machine Learning Engineer
Capital One National Association, Mc Lean, Virginia, us, 22107
Overview
Senior 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, 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. Basic Qualifications
Bachelor’s degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications
1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code 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 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Immigration and Salary
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated based upon hours worked. McLean, VA: Senior Machine Learning Engineer — $158,600 - $181,000 Richmond, VA: Senior Machine Learning Engineer — $144,200 - $164,600 Candidates hired to work in other locations will be subject to the pay range for that location, and the actual amount offered will be in the offer letter. This role is eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan. Benefits and Resources
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits. 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. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace and will consider qualified applicants with a criminal history in accordance with applicable laws. If you require an accommodation to apply, 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 provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com.
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Senior 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, 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. Basic Qualifications
Bachelor’s degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications
1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code 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 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Immigration and Salary
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated based upon hours worked. McLean, VA: Senior Machine Learning Engineer — $158,600 - $181,000 Richmond, VA: Senior Machine Learning Engineer — $144,200 - $164,600 Candidates hired to work in other locations will be subject to the pay range for that location, and the actual amount offered will be in the offer letter. This role is eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan. Benefits and Resources
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits. 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. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace and will consider qualified applicants with a criminal history in accordance with applicable laws. If you require an accommodation to apply, 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 provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com.
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