What are the responsibilities and job description for the Manager, Machine Learning Engineering position at Capital One?
Locations: NY - New York, United States of America, New York, New York
Manager, Machine Learning Engineering
As a Capital One Machine Learning Engineer, 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. Working within an Agile environment, you’ll serve as a technical lead, helping guide 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 develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.
What you’ll do in the role:
Manage a team of engineers with deep experience in machine learning and distributed systems.
Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
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, next generation big data and machine learning applications.
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Use programming languages like Python, Scala, or Java.
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Advocate for software and machine learning engineering best practices.
Function as a technical lead.
Attract, recruit, and support diverse ML engineering talent.
Mentor junior ML engineering talent
Basic Qualifications:
Bachelor’s degree
At least 6 years of experience designing and building data-intensive solutions using
distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems
At least 2 years of people leader experience
Preferred Qualifications:
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
3 years of experience building production-ready data pipelines that feed ML models
3 years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
2 years of experience developing performant, resilient, and maintainable code
2 years of experience with data gathering and preparation for ML models
1 years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
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 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).
Manager, Machine Learning Engineering
As a Capital One Machine Learning Engineer, 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. Working within an Agile environment, you’ll serve as a technical lead, helping guide 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 develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.
What you’ll do in the role:
Manage a team of engineers with deep experience in machine learning and distributed systems.
Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
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, next generation big data and machine learning applications.
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Use programming languages like Python, Scala, or Java.
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Advocate for software and machine learning engineering best practices.
Function as a technical lead.
Attract, recruit, and support diverse ML engineering talent.
Mentor junior ML engineering talent
Basic Qualifications:
Bachelor’s degree
At least 6 years of experience designing and building data-intensive solutions using
distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems
At least 2 years of people leader experience
Preferred Qualifications:
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
3 years of experience building production-ready data pipelines that feed ML models
3 years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
2 years of experience developing performant, resilient, and maintainable code
2 years of experience with data gathering and preparation for ML models
1 years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
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 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).
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