Center 1 (19052), United States of America, McLean, VirginiaSenior Machine Learning EngineerAs 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. Youll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Youll 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. This team participates in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. In this role you will have a direct impact on customers and leverage tools like Python, PySpark, Dask, PyTorch, TensorFlow, AWS (Lambda, Step Functions, EMR, SageMaker), Kubernetes, and Kubeflow.What youll do in the role: <ul><li>The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</li><li>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. </li><li>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).</li><li>Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. </li><li>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. </li><li>Retrain, maintain, and monitor models in production.</li><li>Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>Construct optimized data pipelines to feed ML models. </li><li>Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. </li><li>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. </li><li>Use programming languages like Python, Scala, or Java. </li></ul>Basic Qualifications:<ul><li>Bachelors degree</li><li>At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)</li><li>At least 3 years of experience designing and building data-intensive solutions using distributed computing </li><li>At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) </li><li>At least 1 year of experience productionizing, monitoring, and maintaining models </li></ul>Preferred Qualifications:<ul><li>1+ years of experience building, scaling, and optimizing ML systems</li><li>1+ years of experience with data gathering and preparation for ML models</li><li>2+ years of experience developing performant, resilient, and maintainable code</li><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field </li><li>3+ years of experience with distributed file systems or multi-node database paradigms</li><li>Contributed to open source ML software </li><li>Authored/co-authored a paper on a ML technique, model, or proof of concept</li><li>3+ years of experience building production-ready data pipelines that feed ML models </li><li>Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance </li></ul> At this time, Capital One will not sponsor a new applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning EngineerCandidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidates offer letter.This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<div><div><div><div>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 <a target="_blank" href="https://www.capitalonecareers.com/benefits">Capital One Careers website</a>. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</div></div></div></div>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. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York Citys Fair Chance Act; Philadelphias Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at <a target="_blank" href="mailto:RecruitingAccommodation@capitalone.com">RecruitingAccommodation@capitalone.com</a>. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to <a target="_blank" href="mailto:Careers@capitalone.com">Careers@capitalone.com</a>Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Center 1 (19052), United States of America, McLean, VirginiaSenior Machine Learning Engineer (Python, Spark, MLOPS, Cloud)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. Youll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Youll 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 youll do in the role: <ul><li>The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</li><li>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. </li><li>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).</li><li>Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. </li><li>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. </li><li>Retrain, maintain, and monitor models in production.</li><li>Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>Construct optimized data pipelines to feed ML models. </li><li>Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. </li><li>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. </li><li>Use programming languages like Python, Scala, or Java. </li></ul>Basic Qualifications:<ul><li>Bachelors degree</li><li>At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)</li><li>At least 3 years of experience designing and building data-intensive solutions using distributed computing </li><li>At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) </li><li>At least 1 year of experience productionizing, monitoring, and maintaining models </li></ul>Preferred Qualifications:<ul><li>1+ years of experience building, scaling, and optimizing ML systems</li><li>1+ years of experience with data gathering and preparation for ML models</li><li>2+ years of experience developing performant, resilient, and maintainable code</li><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field </li><li>3+ years of experience with distributed file systems or multi-node database paradigms</li><li>Contributed to open source ML software </li><li>Authored/co-authored a paper on a ML technique, model, or proof of concept</li><li>3+ years of experience building production-ready data pipelines that feed ML models </li><li>Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance </li></ul>At this time, Capital One will not sponsor a new applicant for employment authorization for this position.The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning EngineerCandidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidates offer letter.This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<div><div><div><div>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 <a href="https://www.capitalonecareers.com/benefits" target="_blank">Capital One Careers website</a>. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</div></div></div></div>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. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York Citys Fair Chance Act; Philadelphias Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at <a href="mailto:RecruitingAccommodation@capitalone.com" target="_blank">RecruitingAccommodation@capitalone.com</a>. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to <a href="mailto:Careers@capitalone.com" target="_blank">Careers@capitalone.com</a>Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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