Hobbsnews
Senior Manager, Machine Learning Engineer (People Leader)
Hobbsnews, New York, New York, us, 10261
Overview
Senior Manager, Machine Learning Engineer (People Leader) – Capital One's Digital Commerce & Innovation organization is seeking a Machine Learning Engineer, People Leader at the Senior Manager level to join Velocity Black by Capital One. You will transition from deep technical work with engineers to high-level, strategic discussions and help leverage emerging AI capabilities to reimagine how we serve customers and businesses who rely on Capital One products and services. Velocity Black by Capital One harnesses artificial intelligence, the warmth of human experts, and the latest interfaces to help high-performance people realize their potential. The service uses 24/7 chat, AI, and mobile payments for access to experiences across Travel, Experiences, Luxury Goods, and Dining. Velocity Black is built in React Native with exclusive access and worldwide service; Gravity, our internal request management platform, is built with React and Node.js microservices to augment agents with AI. What you’ll do in the role
The MLE role overlaps with Ops, Modeling, and Data Engineering. In this role, you will perform 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, in collaboration with Product and Data Science teams. Inform ML infrastructure decisions using understanding of modeling techniques and issues, including model choice, data, 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 for state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Follow CI/CD best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure code quality, model governance, and responsible AI practices, including explainability and risk considerations. Use programming languages such as Python, Scala, or Java. Basic Qualifications
Bachelor’s degree At 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 Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions At least 4 years of people management experience Preferred Qualifications
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 4+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Additional notes
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. This salary information is for candidates hired to work in one of these locations and refers to the amount Capital One is willing to pay at the time of the posting. Salaries for part-time roles will be prorated based on hours worked. New York, NY:
$245,900 - $280,600
for Sr. Manager, Machine Learning Engineering. Candidates hired elsewhere will be subject to the pay range for that location, with the offer letter reflecting the actual salary. This role is eligible for performance-based incentive compensation, which may include cash bonuses 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. Learn more at the Capital One Careers website. Eligibility varies based on status and management level. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with laws. Capital One supports a drug-free workplace and will consider qualified applicants with criminal histories as required by law. If you require an accommodation, contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One does not endorse or guarantee third-party products or information available through this site, and Capital One Financial is composed of multiple entities (Canada, Europe, Philippines-specific postings may apply).
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Senior Manager, Machine Learning Engineer (People Leader) – Capital One's Digital Commerce & Innovation organization is seeking a Machine Learning Engineer, People Leader at the Senior Manager level to join Velocity Black by Capital One. You will transition from deep technical work with engineers to high-level, strategic discussions and help leverage emerging AI capabilities to reimagine how we serve customers and businesses who rely on Capital One products and services. Velocity Black by Capital One harnesses artificial intelligence, the warmth of human experts, and the latest interfaces to help high-performance people realize their potential. The service uses 24/7 chat, AI, and mobile payments for access to experiences across Travel, Experiences, Luxury Goods, and Dining. Velocity Black is built in React Native with exclusive access and worldwide service; Gravity, our internal request management platform, is built with React and Node.js microservices to augment agents with AI. What you’ll do in the role
The MLE role overlaps with Ops, Modeling, and Data Engineering. In this role, you will perform 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, in collaboration with Product and Data Science teams. Inform ML infrastructure decisions using understanding of modeling techniques and issues, including model choice, data, 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 for state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Follow CI/CD best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure code quality, model governance, and responsible AI practices, including explainability and risk considerations. Use programming languages such as Python, Scala, or Java. Basic Qualifications
Bachelor’s degree At 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 Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions At least 4 years of people management experience Preferred Qualifications
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 4+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Additional notes
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. This salary information is for candidates hired to work in one of these locations and refers to the amount Capital One is willing to pay at the time of the posting. Salaries for part-time roles will be prorated based on hours worked. New York, NY:
$245,900 - $280,600
for Sr. Manager, Machine Learning Engineering. Candidates hired elsewhere will be subject to the pay range for that location, with the offer letter reflecting the actual salary. This role is eligible for performance-based incentive compensation, which may include cash bonuses 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. Learn more at the Capital One Careers website. Eligibility varies based on status and management level. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with laws. Capital One supports a drug-free workplace and will consider qualified applicants with criminal histories as required by law. If you require an accommodation, contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One does not endorse or guarantee third-party products or information available through this site, and Capital One Financial is composed of multiple entities (Canada, Europe, Philippines-specific postings may apply).
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