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).

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 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).

The Company You’ll Join At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data—over half a billion records of public figures, places, and things, plus a globe-spanning consumer behavior and sentiment database—to unearth deep insights about consumer preferences. From understanding global travel trends to curating <a >the perfect restaurant recommendation </a> based on your unique tastes, our Taste AI engine sifts through the noise to find the signals that matter. And the best part? Qloo's API suite is powered by cultural entities, not personal identities, ensuring our insights are derived <a >without relying on personally identifiable information </a>. Read more about our recent Series C funding <a >here </a>. The team you’ll work with: Reporting directly to the VP of Applied ML, you’ll be an integral part of the Applied Machine Learning (ML) team within the broader AI division. This team sits at the intersection of cutting-edge machine learning and business impact, collaborating closely with the Research & Development side of the AI team, the Data Engineering team, as well as cross-functional stakeholders like Product and Sales. Together, this collaborative environment drives the implementation and scaling of machine learning models to solve real-world problems. You’ll be focused on developing and maintaining models that directly support customer experiences and business goals, and you’ll regularly work across these teams to align the technical aspects of the models with the company’s strategic vision. Hear what the team has to say – “...the fantastic team I work with creates an environment where we encourage each other and collaborate, which naturally leads to creative ideas. The complex technical challenges we face not only keep things interesting but also push us to find unique solutions, and AI constantly inspires me to excel in my role.” - Elizabeth, VP of Applied ML. The impact you’ll have: In this role, you will be responsible for maintaining existing data pipelines and continuously improving the end-to-end modeling process. A key focus will be enhancing and evolving our Geospatial and Taste Analysis models—two cornerstones of the company’s machine learning offerings. The Geospatial models are designed to predict entity affinities within specific regions, while the Taste Analysis models use advanced recommendation techniques to map customer preferences. This position offers an exciting opportunity to take on significant responsibilities, with limited oversight, allowing you to make a major impact on the future of the product. You'll immediately provide value by: <ul><li>Taking ownership of coding and documentation efforts, ensuring best practices and scalability. </li><li>Working on key models such as the Geospatial and Taste Analysis models, driving innovation and optimization. </li><li>Leading the design, rebuild, and improvement of key machine learning pipelines with minimal oversight. </li><li>Operating as a self-motivator who thrives in a collaborative environment, where their contributions can drive significant business impact. </li> </ul>To be a successful match you must have: <ul><li>3+ years of experience in Machine Learning Engineering. </li><li>A degree in Mathematics, Engineering, Statistics, Computer Science, or Physics. Advanced degree preferred but not required. </li><li>Excellent communication, collaboration skills, and ability to dive into the weeds. </li><li>Strong Python, SQL, and/or PySpark skills. </li><li>Ability to work independently and manage multiple projects simultaneously. </li><li>Knowledge and experience with statistical modeling, especially in its application for ML modeling. </li><li>A “can-do” self-starter mentality with the ability to roll-up your sleeves, and thrive in a fast-paced, ambiguous start-up culture. </li> </ul>What we offer: <ul><li>Potential equity package. </li><li>Excellent health insurance coverage, with ability to join group dental and vision for a nominal fee. </li><li>4% 401K matching. </li><li>20 paid time off days. </li><li>5 paid sick days. </li><li>12 weeks of paid parental leave. </li><li>10+ annual company holidays. </li><li>Opportunities for professional development and growth within a dynamic environment. </li><li>A supportive and inclusive company ethos where your ideas are valued, your contributions are recognized, and your impact is tangible. </li><li>The chance to be part of a small but mighty team that's making waves in the industry and shaping the future of technology. </li><li>Beautiful HQ in Soho, NYC with the opportunity to work in-office, if desired. </li> </ul>$110,000 - $180,000 a year Compensation determined based on experience and qualifications. To be discussed during interview process. We are open to different backgrounds and tenure for this hire and compensation will be commensurate with experience. Please note that equity may be included in our total package, depending on role and level. #J-18808-Ljbffr

The Company You’ll JoinAt Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data—over half a billion records of public figures, places, and things, plus a globe-spanning consumer behavior and sentiment database—to unearth deep insights about consumer preferences. From understanding global travel trends to curating <a href="#">the perfect restaurant recommendation</a> based on your unique tastes, our Taste AI engine sifts through the noise to find the signals that matter.And the best part? Qloo's API suite is powered by cultural entities, not personal identities, ensuring our insights are derived <a href="#">without relying on personally identifiable information</a>.Read more about our recent Series C funding <a href="#">here</a>.The team you’ll work with:Reporting directly to the VP of Applied ML, you’ll be an integral part of the Applied Machine Learning (ML) team within the broader AI division. This team sits at the intersection of cutting-edge machine learning and business impact, collaborating closely with the Research & Development side of the AI team, the Data Engineering team, as well as cross-functional stakeholders like Product and Sales. Together, this collaborative environment drives the implementation and scaling of machine learning models to solve real-world problems. You’ll be focused on developing and maintaining models that directly support customer experiences and business goals, and you’ll regularly work across these teams to align the technical aspects of the models with the company’s strategic vision.Hear what the team has to say – “...the fantastic team I work with creates an environment where we encourage each other and collaborate, which naturally leads to creative ideas. The complex technical challenges we face not only keep things interesting but also push us to find unique solutions, and AI constantly inspires me to excel in my role.” - Elizabeth, VP of Applied ML.The impact you’ll have:In this role, you will be responsible for maintaining existing data pipelines and continuously improving the end-to-end modeling process. A key focus will be enhancing and evolving our Geospatial and Taste Analysis models—two cornerstones of the company’s machine learning offerings. The Geospatial models are designed to predict entity affinities within specific regions, while the Taste Analysis models use advanced recommendation techniques to map customer preferences. This position offers an exciting opportunity to take on significant responsibilities, with limited oversight, allowing you to make a major impact on the future of the product.You'll immediately provide value by:<ul><li>Taking ownership of coding and documentation efforts, ensuring best practices and scalability.</li><li>Working on key models such as the Geospatial and Taste Analysis models, driving innovation and optimization.</li><li>Leading the design, rebuild, and improvement of key machine learning pipelines with minimal oversight.</li><li>Operating as a self-motivator who thrives in a collaborative environment, where their contributions can drive significant business impact.</li></ul>To be a successful match you must have:<ul><li>3+ years of experience in Machine Learning Engineering.</li><li>A degree in Mathematics, Engineering, Statistics, Computer Science, or Physics. Advanced degree preferred but not required.</li><li>Excellent communication, collaboration skills, and ability to dive into the weeds.</li><li>Strong Python, SQL, and/or PySpark skills.</li><li>Ability to work independently and manage multiple projects simultaneously.</li><li>Knowledge and experience with statistical modeling, especially in its application for ML modeling.</li><li>A “can-do” self-starter mentality with the ability to roll-up your sleeves, and thrive in a fast-paced, ambiguous start-up culture.</li></ul>What we offer:<ul><li>Potential equity package.</li><li>Excellent health insurance coverage, with ability to join group dental and vision for a nominal fee.</li><li>4% 401K matching.</li><li>20 paid time off days.</li><li>5 paid sick days.</li><li>12 weeks of paid parental leave.</li><li>10+ annual company holidays.</li><li>Opportunities for professional development and growth within a dynamic environment.</li><li>A supportive and inclusive company ethos where your ideas are valued, your contributions are recognized, and your impact is tangible.</li><li>The chance to be part of a small but mighty team that's making waves in the industry and shaping the future of technology.</li><li>Beautiful HQ in Soho, NYC with the opportunity to work in-office, if desired.</li></ul><div>$110,000 - $180,000 a year</div><div>Compensation determined based on experience and qualifications. To be discussed during interview process.</div>We are open to different backgrounds and tenure for this hire and compensation will be commensurate with experience. Please note that equity may be included in our total package, depending on role and level.
#J-18808-Ljbffr

Center 1 (19052), United States of America, McLean, VirginiaSenior Machine Learning Engineer (Remote-Eligible)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. Capital One is open to hiring a Remote Employee for this opportunityBasic Qualifications:Bachelor''s degree. At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications:1+ years of experience building, scaling, and optimizing ML systems1+ years of experience with data gathering and preparation for ML models2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud PlatformMaster''s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization for this position.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, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, 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 [Click Here to Email Your Resum]. 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 [Click Here to Email Your Resum]Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Center 1 (19052), United States of America, McLean, VirginiaSenior Machine Learning Engineer (Remote-Eligible)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. Capital One is open to hiring a Remote Employee for this opportunityBasic Qualifications:Bachelor''s degree. At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications:1+ years of experience building, scaling, and optimizing ML systems1+ years of experience with data gathering and preparation for ML models2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud PlatformMaster''s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization for this position.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, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, 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 [Click Here to Email Your Resum]. 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 [Click Here to Email Your Resum]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 Elizabeth, NJ

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Machine Learning Engineer Jobs in Elizabeth, NJ

Machine Learning EngineerDecember 10, 2024

Machine Learning EngineerDecember 9, 2024

Machine Learning EngineerDecember 9, 2024

Machine Learning EngineerDecember 8, 2024

Senior Machine Learning Engineer RemoteeligibleDecember 3, 2024

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Machine Learning Engineer Summer Intern Remote PaidNovember 30, 2024

Quick filters

Top companies

Machine Learning Engineer
December 10, 2024

Machine Learning Engineer
December 9, 2024

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December 9, 2024

Machine Learning Engineer
December 8, 2024

Senior Machine Learning Engineer Remoteeligible
December 3, 2024

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Senior Machine Learning Engineer Remoteeligible
December 1, 2024

Machine Learning Engineer Summer Intern Remote Paid
November 30, 2024