Hispanic Technology Executive Council
Senior Manager, Machine Learning Engineering - Capital One Software (Remote)
Hispanic Technology Executive Council, Virginia, Minnesota, United States, 55792
Locations: US Remote, United States of AmericaSenior Manager, Machine Learning Engineering - Capital One Software (Remote)
Ever since our first credit card customer in 1994, Capital One has recognized that technology and data can enable even large companies to be innovative and personalized. As one of the first large enterprises to go all-in on the public cloud, Capital One needed to build cloud and data management tools that didn't exist in the marketplace to enable us to operate at scale in the cloud. And in 2022, we publicly announced Capital One Software and brought our first B2B software solution, Slingshot, to market.Building on Capital One's pioneering adoption of modern cloud and data capabilities, Capital One Software is helping accelerate the data management journey at scale for businesses operating in the cloud. If you think of the kind of challenges that companies face - things like data publishing, data consumption, data governance, and infrastructure management - we've built tools to address these various needs along the way.We are seeking top tier talent to join our pioneering team and propel us towards our destination. You will be joining a team of innovative product, tech, and design leaders that tirelessly seek to question the status quo. As a Capital One Senior Manager, Machine Learning Engineering, you'll have the opportunity to be on the forefront of building this business and bring these tools to market.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 degreeAt least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)At least 4 years of experience programming with Python, Scala, or JavaAt least 3 years of experience building, scaling, and optimizing ML systemsAt least 2 years of experience leading teams developing ML solutionsAt least 4 years of people management experience.Preferred Qualifications:
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow3+ years of experience developing performant, resilient, and maintainable code3+ years of experience with data gathering and preparation for ML modelsExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform3+ years of experience building production-ready data pipelines that feed ML modelsAbility to communicate complex technical concepts clearly to a variety of audiencesML industry impact through conference presentations, papers, blog posts, open source contributions, or patentsAt 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.Remote (Regardless of Location): $198,900 - $227,000 for Sr. Mgr, Machine Learning EngineeringThis 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.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
#J-18808-Ljbffr
Ever since our first credit card customer in 1994, Capital One has recognized that technology and data can enable even large companies to be innovative and personalized. As one of the first large enterprises to go all-in on the public cloud, Capital One needed to build cloud and data management tools that didn't exist in the marketplace to enable us to operate at scale in the cloud. And in 2022, we publicly announced Capital One Software and brought our first B2B software solution, Slingshot, to market.Building on Capital One's pioneering adoption of modern cloud and data capabilities, Capital One Software is helping accelerate the data management journey at scale for businesses operating in the cloud. If you think of the kind of challenges that companies face - things like data publishing, data consumption, data governance, and infrastructure management - we've built tools to address these various needs along the way.We are seeking top tier talent to join our pioneering team and propel us towards our destination. You will be joining a team of innovative product, tech, and design leaders that tirelessly seek to question the status quo. As a Capital One Senior Manager, Machine Learning Engineering, you'll have the opportunity to be on the forefront of building this business and bring these tools to market.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 degreeAt least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)At least 4 years of experience programming with Python, Scala, or JavaAt least 3 years of experience building, scaling, and optimizing ML systemsAt least 2 years of experience leading teams developing ML solutionsAt least 4 years of people management experience.Preferred Qualifications:
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow3+ years of experience developing performant, resilient, and maintainable code3+ years of experience with data gathering and preparation for ML modelsExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform3+ years of experience building production-ready data pipelines that feed ML modelsAbility to communicate complex technical concepts clearly to a variety of audiencesML industry impact through conference presentations, papers, blog posts, open source contributions, or patentsAt 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.Remote (Regardless of Location): $198,900 - $227,000 for Sr. Mgr, Machine Learning EngineeringThis 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.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
#J-18808-Ljbffr