Capital One
Senior Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS)
Capital One, Mc Lean, Virginia, us, 22107
Overview
Senior Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS) – part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You will participate in the technical design, development, and implementation of machine learning applications using existing and emerging technology platforms, focusing on ML architectural design, code reviews, and ensuring high availability and performance of ML applications. You will have opportunities to continuously learn and apply the latest innovations and best practices in ML engineering. Responsibilities
The MLE role overlaps with multiple disciplines, including Operations, Modeling, and Data Engineering. You will perform various 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, collaborating with Product and Data Science teams. Inform ML infrastructure decisions using understanding of modeling techniques, 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 enabling state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Adopt continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows practices in Responsible and Explainable AI. Use programming languages such as Python, Scala, or Java. Basic Qualifications
Bachelor's degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications
1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on an ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Note:
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 are provided for candidates hired to work within one of these locations and refer to the amount Capital One is willing to pay at the time of posting. Salaries for part-time roles will be prorated based upon hours worked. McLean, VA: $158,600 - $181,000 for Senior Machine Learning Engineer New York, NY: $173,000 - $197,400 for Senior Machine Learning Engineer Richmond, VA: $144,200 - $164,600 for Senior Machine Learning Engineer San Francisco, CA: $173,000 - $197,400 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered will be reflected in the offer letter. 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. Learn more at the Capital One Careers website. Eligibility varies based on full/part-time status, exempt/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 (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 in a manner consistent with applicable laws regarding criminal background inquiries. If you require an accommodation during the application process, please 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 questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One does not provide, endorse nor guarantee third-party products or information available through this site. Capital One Financial is made up of several entities; positions posted in Canada, the United Kingdom, or the Philippines correspond to Capital One Canada, Capital One Europe, or Capital One Philippines Service Corp. respectively.
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Senior Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS) – part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You will participate in the technical design, development, and implementation of machine learning applications using existing and emerging technology platforms, focusing on ML architectural design, code reviews, and ensuring high availability and performance of ML applications. You will have opportunities to continuously learn and apply the latest innovations and best practices in ML engineering. Responsibilities
The MLE role overlaps with multiple disciplines, including Operations, Modeling, and Data Engineering. You will perform various 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, collaborating with Product and Data Science teams. Inform ML infrastructure decisions using understanding of modeling techniques, 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 enabling state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Adopt continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows practices in Responsible and Explainable AI. Use programming languages such as Python, Scala, or Java. Basic Qualifications
Bachelor's degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications
1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on an ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Note:
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 are provided for candidates hired to work within one of these locations and refer to the amount Capital One is willing to pay at the time of posting. Salaries for part-time roles will be prorated based upon hours worked. McLean, VA: $158,600 - $181,000 for Senior Machine Learning Engineer New York, NY: $173,000 - $197,400 for Senior Machine Learning Engineer Richmond, VA: $144,200 - $164,600 for Senior Machine Learning Engineer San Francisco, CA: $173,000 - $197,400 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered will be reflected in the offer letter. 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. Learn more at the Capital One Careers website. Eligibility varies based on full/part-time status, exempt/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 (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 in a manner consistent with applicable laws regarding criminal background inquiries. If you require an accommodation during the application process, please 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 questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One does not provide, endorse nor guarantee third-party products or information available through this site. Capital One Financial is made up of several entities; positions posted in Canada, the United Kingdom, or the Philippines correspond to Capital One Canada, Capital One Europe, or Capital One Philippines Service Corp. respectively.
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