Capital One
Lead Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS)
Capital One, New York, New York, us, 10261
Overview
Lead Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS) at Capital One. You’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale, contributing to detailed technical design, development, and implementation of ML applications using existing and emerging technology platforms. The role focuses on ML architectural design, developing and reviewing model and application code, and ensuring high availability and performance of ML applications. You’ll have opportunities to continuously learn and apply the latest innovations and best practices in ML 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 collaborating with Product and Data Science teams. Inform ML infrastructure decisions using understanding of ML modeling techniques and issues, including choice of model, 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 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 6 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 2 years of experience building, scaling, and optimizing ML systems 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 2+ years of people leader experience 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, or offer any immigration related support for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated based upon hours worked. Note on locations and salary disclosures
Capital One provides salary ranges by location and states that actual offers reflect the candidate’s location and other factors. This section contains salary ranges by location for Lead Machine Learning Engineer roles and related guidance. This section is for disclosure purposes in the posting and may not reflect the final offer. This role is also eligible to earn 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. Eligibility varies by status and 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 (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with a criminal history consistent with applicable laws. If you require accommodations to apply, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. Capital One is made up of several entities. Positions posted in Canada are for Capital One Canada, in the United Kingdom for Capital One Europe, and in the Philippines for Capital One Philippines Service Corp. (COPSSC).
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Lead Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS) at Capital One. You’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale, contributing to detailed technical design, development, and implementation of ML applications using existing and emerging technology platforms. The role focuses on ML architectural design, developing and reviewing model and application code, and ensuring high availability and performance of ML applications. You’ll have opportunities to continuously learn and apply the latest innovations and best practices in ML 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 collaborating with Product and Data Science teams. Inform ML infrastructure decisions using understanding of ML modeling techniques and issues, including choice of model, 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 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 6 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 2 years of experience building, scaling, and optimizing ML systems 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 2+ years of people leader experience 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, or offer any immigration related support for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated based upon hours worked. Note on locations and salary disclosures
Capital One provides salary ranges by location and states that actual offers reflect the candidate’s location and other factors. This section contains salary ranges by location for Lead Machine Learning Engineer roles and related guidance. This section is for disclosure purposes in the posting and may not reflect the final offer. This role is also eligible to earn 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. Eligibility varies by status and 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 (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with a criminal history consistent with applicable laws. If you require accommodations to apply, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. Capital One is made up of several entities. Positions posted in Canada are for Capital One Canada, in the United Kingdom for Capital One Europe, and in the Philippines for Capital One Philippines Service Corp. (COPSSC).
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