Company Description

Jobs for Humanity is partnering with Capital One to build an inclusive and just employment ecosystem. Therefore, we prioritize individuals coming from the following communities: Refugee, Neurodivergent, Single Parent, Blind or Low Vision, Deaf or Hard of Hearing, Black, Hispanic, Asian, Military Veterans, the Elderly, the LGBTQ, and Justice Impacted individuals. This position is open to candidates who reside in and have the legal right to work in the country where the job is located.

Company Name: Capital One

Job Description

Center 1 (19052), United States of America, McLean, Virginia

Senior Machine Learning Engineer

Do you have a passion for Machine Learning and AI? Do you enjoy solving complex business problems by constantly learning new technologies and employing your skills to make a meaningful impact? 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. You ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. 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. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

We are looking for a motivated and self organized Machine Learning Engineer who can build and deliver state of the art batch, streaming and real time ML and AI solutions to join the Marketing program to drive powerful experiences for our users. In this role, you will be responsible for various activities in all phases of the model lifecycle such as feature and model development, model validation, build and deploy scoring pipelines, create monitoring solutions, integrate solutions with Marketing platforms and leverage AWS platform to deliver optimized ML solutions at scale.

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 working in collaboration with the Product and Data Science teams.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).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 3 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 JavaAt least 2 years of on-the-job experience with an industry recognized 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 systems1+ years of experience with data gathering and preparation for ML models2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWSMaster's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML softwareAuthored/co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML modelsExperience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or 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 committed to diversity and inclusion in the workplace. 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. 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.

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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).#J-18808-Ljbffr