Plano 1 (31061), United States of America, Plano, TexasDistinguished Machine Learning Engineer (Director IC)At Capital One, we believe that machine learning represents the biggest opportunity in financial services today, and is a chance to revolutionize the industry. Capital One’s commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company. The Center for Machine Learning is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML.  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.About the team: As part of FS AI labs you will be working on AI initiatives within Financial Services with a focus on Applied AI and Machine Learning (AI/ML), Generative AI, Natural Language Processing (NLP), and Responsible AI. The primary objective of FS AI Labs is to drive the research and delivery of innovative AI and ML use cases that leverage these cutting-edge technologies. You will work on exploring new frontiers, build prototypes, and deliver transformative AI use cases that drive Capital One Financial Services business growth and enhance customer experience.What you’ll do in the role:<ul><li>Lead large-scale ML initiatives with the customer in mind.</li><li>Lead the development of AI and ML use cases that leverage state of art AI and ML techniques, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.</li><li>Stay abreast of the latest advancements in Generative AI, Large Language Models, NLP. Drive research efforts to identify new opportunities and use cases, pushing the boundaries based on feasibility.</li><li>Collaborate with business stakeholders to understand the needs and identify opportunities where AI can be applied. </li><li>Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.</li><li>Evangelize best practices in all aspects of the AI/ML 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 degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques.</li><li>Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM fine-tuning, LLM Evaluation.</li><li>Experience developing AI and ML algorithms in Python or C/C++</li><li>Experience with building LLM based chatbots in production including experience with developing multi turn and agentic workflows and LLM pre training.</li><li>Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.</li><li>Experience leveraging a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data</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> 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 <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.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).

Plano 1 (31061), United States of America, Plano, Texas Distinguished Machine Learning Engineer (Director IC) At Capital One, we believe that machine learning represents the biggest opportunity in financial services today, and is a chance to revolutionize the industry. Capital Ones commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company. The Center for Machine Learning is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML. 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. Youll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Youll 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. Youll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology. About the team: As part of FS AI labs you will be working on AI initiatives within Financial Services with a focus on Applied AI and Machine Learning (AI/ML), Generative AI, Natural Language Processing (NLP), and Responsible AI. The primary objective of FS AI Labs is to drive the research and delivery of innovative AI and ML use cases that leverage these cutting-edge technologies. You will work on exploring new frontiers, build prototypes, and deliver transformative AI use cases that drive Capital One Financial Services business growth and enhance customer experience. What youll do in the role: <ul> <li>Lead large-scale ML initiatives with the customer in mind. </li> <li>Lead the development of AI and ML use cases that leverage state of art AI and ML techniques, working in collaboration with the Product, Architecture, Engineering, and Data Science teams. </li> <li>Stay abreast of the latest advancements in Generative AI, Large Language Models, NLP. Drive research efforts to identify new opportunities and use cases, pushing the boundaries based on feasibility. </li> <li>Collaborate with business stakeholders to understand the needs and identify opportunities where AI can be applied. </li> <li>Leverage cloud-based architectures and technologies to deliver optimized ML models at scale. </li> <li>Evangelize best practices in all aspects of the AI/ML engineering and modeling lifecycles. </li> <li>Help recruit, nurture, and retain top engineering talent. </li> </ul>Basic Qualifications <ul> <li>Bachelors 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>Masters degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. </li> <li>Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM fine-tuning, LLM Evaluation. </li> <li>Experience developing AI and ML algorithms in Python or C/C++ </li> <li>Experience with building LLM based chatbots in production including experience with developing multi turn and agentic workflows and LLM pre training. </li> <li>Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms. </li> <li>Experience leveraging a broad stack of technologies Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more to reveal the insights hidden within huge volumes of numeric and textual data </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> 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 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 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).

Plano 1 (31061), United States of America, Plano, TexasDistinguished Machine Learning Engineer (Director IC)At Capital One, we believe that machine learning represents the biggest opportunity in financial services today, and is a chance to revolutionize the industry. Capital Ones commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company. The Center for Machine Learning is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML. 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. Youll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Youll 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. Youll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.About the team: As part of FS AI labs you will be working on AI initiatives within Financial Services with a focus on Applied AI and Machine Learning (AI/ML), Generative AI, Natural Language Processing (NLP), and Responsible AI. The primary objective of FS AI Labs is to drive the research and delivery of innovative AI and ML use cases that leverage these cutting-edge technologies. You will work on exploring new frontiers, build prototypes, and deliver transformative AI use cases that drive Capital One Financial Services business growth and enhance customer experience.What youll do in the role:<ul><li>Lead large-scale ML initiatives with the customer in mind.</li><li>Lead the development of AI and ML use cases that leverage state of art AI and ML techniques, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.</li><li>Stay abreast of the latest advancements in Generative AI, Large Language Models, NLP. Drive research efforts to identify new opportunities and use cases, pushing the boundaries based on feasibility.</li><li>Collaborate with business stakeholders to understand the needs and identify opportunities where AI can be applied. </li><li>Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.</li><li>Evangelize best practices in all aspects of the AI/ML engineering and modeling lifecycles.</li><li>Help recruit, nurture, and retain top engineering talent.</li></ul>Basic Qualifications<ul><li>Bachelors 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>Masters degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques.</li><li>Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM fine-tuning, LLM Evaluation.</li><li>Experience developing AI and ML algorithms in Python or C/C++</li><li>Experience with building LLM based chatbots in production including experience with developing multi turn and agentic workflows and LLM pre training.</li><li>Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.</li><li>Experience leveraging a broad stack of technologies Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more to reveal the insights hidden within huge volumes of numeric and textual data</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> 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 <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.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).

Center 3 (19075), 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. 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, 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).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.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).

Center 3 (19075), United States of America, McLean, VirginiaSenior 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 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, 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). 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).

Machine Learning Engineer Jobs in Wichita Falls, TX

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Senior Machine Learning Engineer
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Machine Learning Engineer Jobs in Wichita Falls, TX

Distinguished Machine Learning Engineer Director IcDecember 21, 2024

Distinguished Machine Learning Engineer Director IcDecember 11, 2024

Distinguished Machine Learning Engineer Director IcDecember 10, 2024

Senior Machine Learning EngineerDecember 10, 2024

Senior Machine Learning EngineerDecember 8, 2024

Distinguished Machine Learning Engineer Director IcNovember 26, 2024

Senior Machine Learning EngineerNovember 26, 2024