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The Senior Machine Learning Operations Engineer will be part of the Johns Hopkins Medicine Technology Innovation Center and will work full-time with the Precision Medicine team (as well as clients, data stewards, project/program managers, and other IT teams.
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New York City (Hybrid On-Site): $165,100 - $188,500 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 to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
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Locations: NY - New York, United States of America, New York, New York Senior Machine Learning Engineer Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
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New York City (Hybrid On-Site): $161,900 - $184,800 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 to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
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Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
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Center 1 (19052), United States of America, McLean, Virginia Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
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You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
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You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
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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. The minimum and maximum full-time annual salaries for this role are listed below, by location.
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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.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). What you’ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering.
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Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. 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.
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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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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.
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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.
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part time jobs Title: senior machine learning engineer
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