<div id="sajCpTopImage"></div><div id="sajCpCustomDescription">Center 3 (19075), United States of America, McLean, VirginiaMachine 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.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 2 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>At least 2 years of experience programming with Python, Scala, or Java</li><li>At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)</li></ul>Preferred Qualifications:<ul><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>1+ years of experience working with large code bases in a team environment</li><li>1+ years of experience with distributed file systems</li><li>1+ years of experience building production-ready data pipelines that feed ML models</li><li>1+ years of experience with statistics</li></ul>At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization).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): $138,500 - $158,100 for 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.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital 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. 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 ; 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 or via email at . 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 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).</div><div id="sajCpQualifications"><div id="sajCpQualificationsRequired"><h3 class="jobOverviewSubtitle">Required</h3><ul></ul></div><div id="sajCpQualificationsPreferred"><h3 class="jobOverviewSubtitle">Preferred</h3><ul></ul></div></div><div id="sajCpIndustries"><h3 class="jobOverviewSubtitle">Job Industries</h3><ul><li><a id="sajCpSingleIndustryLink" href="https://www.snagajob.com//job-search/q-Other">Other</a></li></ul></div>

<div id="sajCpTopImage"></div><div id="sajCpCustomDescription">Center 3 (19075), United States of America, McLean, VirginiaMachine 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.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 2 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>At least 2 years of experience programming with Python, Scala, or Java</li><li>At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)</li></ul>Preferred Qualifications:<ul><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>1+ years of experience working with large code bases in a team environment</li><li>1+ years of experience with distributed file systems</li><li>1+ years of experience building production-ready data pipelines that feed ML models</li><li>1+ years of experience with statistics</li></ul>At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization).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): $138,500 - $158,100 for 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 theCapital One Careers website. 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 or via email at . 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 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).</div><div id="sajCpQualifications"><div id="sajCpQualificationsRequired"><h3 class="jobOverviewSubtitle">Required</h3><ul></ul></div><div id="sajCpQualificationsPreferred"><h3 class="jobOverviewSubtitle">Preferred</h3><ul></ul></div></div><div id="sajCpIndustries"><h3 class="jobOverviewSubtitle">Job Industries</h3><ul><li><a id="sajCpSingleIndustryLink" href="https://www.snagajob.com//job-search/q-Other">Other</a></li></ul></div>

Center 3 (19075), United States of America, McLean, VirginiaMachine 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. 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: <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>Bachelor’s degree </li><li>At least 2 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>At least 2 years of experience programming with Python, Scala, or Java </li><li>At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) </li></ul>Preferred Qualifications:<ul><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform </li><li>1+ years of experience working with large code bases in a team environment</li><li>1+ years of experience with distributed file systems </li><li>1+ years of experience building production-ready data pipelines that feed ML models</li><li>1+ years of experience with statistics </li></ul>At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization).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): $138,500 - $158,100 for 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 candidate’s 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 City’s Fair Chance Act; Philadelphia’s 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).

Center 3 (19075), United States of America, McLean, Virginia 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:  <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>Bachelor’s degree  </li> <li>At least 2 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) </li> <li>At least 2 years of experience programming with Python, Scala, or Java  </li> <li>At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)  </li> </ul>Preferred Qualifications: <ul> <li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform  </li> <li>1+ years of experience working with large code bases in a team environment </li> <li>1+ years of experience with distributed file systems  </li> <li>1+ years of experience building production-ready data pipelines that feed ML models </li> <li>1+ years of experience with statistics  </li> </ul>At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization). 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): $138,500 - $158,100 for Machine Learning Engineer Candidates 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 candidate’s 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. 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. 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 City’s Fair Chance Act; Philadelphia’s 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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com 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, VirginiaDistinguished Machine Learning Engineer As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams 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 serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring 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. You’ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology. In this role, you will be supporting the Bank Tech organization. You will lead development and implementation that will enable business initiatives, working with other leaders and teams across the enterprise to enable these solutions. . What you’ll do in the role: <ul> <li>Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams. </li> <li>Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems. </li> <li>Lead large-scale ML initiatives with the customer in mind. </li> <li>Leverage cloud-based architectures and technologies to deliver optimized ML models at scale. </li> <li>Optimize data pipelines to feed ML models. </li> <li>Use programming languages like Python, Scala, C/C++. </li> <li>Leverage compute technologies such as Dask and RAPIDS </li> <li>Evangelize best practices in all aspects of the engineering and modeling lifecycles. </li> <li>Help recruit, nurture, and retain top engineering talent. </li> </ul>Basic Qualifications <ul> <li>Bachelor’s degree. </li> <li>At least 10 years of experience designing and building data-intensive solutions using distributed computing. </li> <li>At least 6 years of experience programming in C, C++, Python, or Scala. </li> <li>At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting. </li> <li>At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing </li> <li>At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn) </li> </ul>Preferred Qualifications <ul> <li>Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field. </li> <li>3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models. </li> <li>8+ years of experience within a large/data-intensive multi-line business environment. </li> <li>Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms. </li> <li>Ability to communicate complex technical concepts clearly to a variety of audiences. </li> <li>ML industry impact through conference presentations, papers, blog posts, or open source contributions. </li> <li>Ability to attract and develop high-performing software engineers with an inspiring leadership style. </li> </ul>At this time, Capital One will 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): $274,800 - $313,600 for Distinguished Machine Learning Engineer Candidates 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 candidate’s 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. 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. 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 City’s Fair Chance Act; Philadelphia’s 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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com 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 3 (19075), United States of America, McLean, Virginia 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: 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: 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. Basic Qualifications: Bachelor’s degree At least 2 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 2 years 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 1 years of experience working with large code bases in a team environment 1 years of experience with distributed file systems 1 years of experience building production-ready data pipelines that feed ML models 1 years of experience with statistics At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization). 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): $138,500 - $158,100 for Machine Learning Engineer Candidates 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 candidate’s 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. 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. 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 City’s Fair Chance Act; Philadelphia’s 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 RecruitingAccommodationcapitalone.com . 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 Careerscapitalone.com 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 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: <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> 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: <ul> <li>Bachelor’s degree </li><li> At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) </li> <li>At least 4 years of experience programming with Python, Scala, or Java </li><li> At least 3 years of experience building, scaling, and optimizing ML systems </li> <li>At least 2 years of experience leading teams developing ML solutions </li></ul> Preferred Qualifications: <ul> <li>Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field </li> <li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform </li><li> 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow </li><li> 3+ years of experience developing performant, resilient, and maintainable code </li> <li>3+ years of experience with data gathering and preparation for ML models </li> <li>3+ years of people management experience </li><li> ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents </li> <li>3+ years of experience building production-ready data pipelines that feed ML models </li><li> Ability to communicate complex technical concepts clearly to a variety of audiences </li></ul> Capital 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. 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 City’s Fair Chance Act; Philadelphia’s 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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com 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 3 (19075), United States of America, McLean, VirginiaMachine 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. 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: 

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:


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. 



Basic Qualifications:

Bachelor’s degree 


At least 2 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)


At least 2 years 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 


1+ years of experience working with large code bases in a team environment


1+ years of experience with distributed file systems 


1+ years of experience building production-ready data pipelines that feed ML models


1+ years of experience with statistics 



At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization).

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): $138,500 - $158,100 for 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 candidate’s 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.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. 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 City’s Fair Chance Act; Philadelphia’s 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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com

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).

Company DescriptionExperian is the world's leading global information services company. During life's big moments – from buying a home or a car, to sending a child to college, to growing a business by connecting with new customers – we empower consumers and our clients to manage their data with confidence. We help individuals to take financial control and access financial services, businesses to make smarter decisions and thrive, lenders to lend more responsibly, and organizations to prevent identity fraud and crime.We're focused on powering opportunities; that's why our Experian Summer Internship Program offers students nationwide a chance to gain hands-on work experience by applying their formal education to solve meaningful projects. During the Summer Internship Program, you will be immersed in Experian's 'People First' philosophy, experiencing our commitment to developing its people.Join us and explore your potential in one of the Top 100 Summer Internship Programs!Job DescriptionThe Machine Learning Engineer Intern will work under the Sr. Manager of Data Science Product Enablement/Adaption. You will support GenAI projects, including developing AI use cases.Responsibilities:<ul><li>Develop tools for operational efficiency and monitoring</li><li>Improve automation and test coverage</li><li>Analyze cost efficiency for infrastructure</li><li>Augment project modules</li></ul>Qualifications<ul><li>Currently enrolled in a Bachelor's degree program or above in math, CS, or related field</li><li>Returning to school in Fall 2025 to complete degree</li><li>GenAI experience preferred, experience in programming languages such as Java, Python, C++</li></ul>Perks:<ul><li>Fully remote</li><li>Volunteer Time Off</li><li>Great compensation</li><li>Flexible work schedule</li><li>Eligible for 401(k) participation in 90 days</li></ul>Additional InformationOur uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; Great Place To Work™ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few. Check out Experian Life on social or our Careers Site to understand why.Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Machine Learning Engineer Jobs in Williamsburg, VA

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Machine Learning Engineer Jobs in Williamsburg, VA

Capital One Machine Learning EngineerDecember 17, 2024

Machine Learning EngineerDecember 15, 2024

Machine Learning EngineerDecember 14, 2024

Machine Learning EngineerDecember 10, 2024

Distinguished Machine Learning EngineerDecember 9, 2024

Machine Learning EngineerDecember 9, 2024

Senior Lead Machine Learning EngineerDecember 6, 2024

Machine Learning EngineerDecember 5, 2024

Machine Learning Engineer Summer Intern Remote PaidNovember 30, 2024