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).

<p>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).</p>

<p>Altice USA Altice USA is a cutting-edge communications, media, and tech company. We connect people to what matters most to them; texting with friends, advertising that resonates, or binge watching their favorite show. Our differentiated approach centers around technologies that push the envelope and deliver the ultimate customer experience. We're building a workforce that attracts and retains the best talent, not only to meet the needs of our customers, but that also reflects the diverse communities we serve. Job Summary Machine Learning Engineers work to deploy end-to-end solutions to business problems leveraging AI and/or ML principles as needed to create those solutions. MLEs will take requests from stakeholders, define the components required for the project, gather data necessary for project EDA and training, then work with stakeholders to develop a plan around the productionized use of the solution, and work to put that solution into final production. Responsibilities Consult with stakeholders to gather business requirements, translate them into data solutions, design high-level model structures and demonstrate deep expertise in advanced analytics techniques (e.g., AI and ML) to design, prototype, and build solutions to business problems Lead communication with other stakeholders to drive use case development and manage expectations on model limitations and lead times Analyze data to identify useful relations, patterns and features that are predictive of user behaviors, preferences, intents, interests Manage and execute entire projects from start to finish, including cross-functional project management; data collection and manipulation, analysis and modeling; communication of insights and recommendations; productionalization of final model products Share findings with stakeholders to improve business decisions and/or influence strategic direction. Monitor and stay updated with industry trends and emerging technologies to identify opportunities for innovation and improvement Developing and maintaining the end to end modeling code and standardizing the code for reusability in the production environment. Profiling users including customer segmentation to help the marketing team to target specific audience for upgrading to services and also for the user retention Qualifications Degree in a quantitative discipline, such as Data Science, Applied Mathematics, Statistics, Economics, Operations Research, Computer Science, Mathematics, Physics, Biology, Chemistry or Engineering. An advanced degree, Data Science bootcamp or MOOC certification is a plus. 3-5 years of work experience in classification, regression, clustering, natural language processing NLP, experiments, and optimization. Ability to apply Bayesian inference, frequentist statistics, causal modeling, and / or machine learning techniques. Experience with any of these: customer segmentation, campaign targeting and effectiveness, A/B experiments, quasi-experiments, sales forecasting, churn propensity modeling, customer lifetime value analysis, credit risk, geospatial analytics, survey key-drivers, marketing mix modeling, multi-touch attribution, or recommender systems. Highly skilled in R and Python for statistical and machine learning programming. Highly skilled in SQL & Python coding to wrangle and explore structured & unstructured data. Proficient with server or Cloud computing platforms, such as Google Compute Engine or EC2. Proficient with data warehouses, such as Oracle, Big Query, or AWS. Subject matter scientist that can review the literature to identify state of the art solutions to a business problem. Altice USA is an Equal Opportunity Employer committed to recruiting, hiring and promoting qualified people of all backgrounds regardless of gender, race, color, creed, national origin, religion, age, marital status, pregnancy, physical or mental disability, sexual orientation, gender identity, military or veteran status, or any other basis protected by federal, state, or local law. Altice USA, Inc. collects personal information about its applicants for employment that may include personal identifiers, professional or employment related information, photos, education information and/or protected classifications under federal and state law. This information is collected for employment purposes, including identification, work authorization, FCRA-compliant background screening, human resource administration and compliance with federal, state and local law. Applicants for employment with Altice will never be asked to provide money (even if reimbursable) as part of the job application or hiring process. Please review our Fraud FAQfor further details. This position is identified as being performed in/or reporting to company operations in New York State. Salary ranges are supplied in compliance with New York State law. Pay is competitive and based on a number of job-related factors, including skills and experience. The starting pay rate/range at time of hire for this position in the posted location is $156,774.00-$198,273.00/year. The rate/range provided herein is the anticipated pay at the time of hire, and does not reflect future job opportunity. We are an Equal Opportunity Employer M/F/Disability/Vet and maintain a drug-free and smoke-free workplace Minimum Salary: 156774.00 Maximum Salary: 198273.00 Salary Unit: Yearly</p>

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