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Center 3 (19075), United States of America, McLean, VirginiaLead Machine Learning Engineer (Intelligent Foundations and Experiences)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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Job title: Senior Machine Learning EngineerJob Description:As a Machine Learning Engineer (MLE), you'll be part of a lean software team dedicated to productionizing machine learning applications and systems at scale.
$130,400 - $217,400Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The Intelligent Foundations and Experiences (IFX) organization delivers exceptional technology, products, services and processes to support our Data and Machine Learning ecosystems and core functions that support holistic operations for Capital One as an enterprise.
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Job Description: Data Engineer Tech stack: Python, PySpark, AWS Responsibilities: Development and maintenance of data pipelines using Python, PySpark and various AWS services. Job Description: Data Engineer Tech stack: Python, PySpark, AWS Responsibilities: Development and maintenance of data pipelines using Python, PySpark and various AWS services.
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The Machine Learning Experience (MLX) team supports an internally hosted Model Training ecosystem running critical infrastructure for machine learning and data analysis across Capital One. You will get an opportunity to collaborate on the 1000's of models being trained on the platform by 4000+ users and dive deep into the unique engineering challenges we have around compute, data access, security and scale.
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We're looking for candidates who are passionate about exploring cutting-edge literature and technologies in machine learning, analytics, and data engineering to enhance our transactional systems excellence.
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The company applies proprietary machine-learning algorithms and data processing resources to measure travel patterns of vehicles, bicycles and pedestrians that enable complex transportation problem solving using analytics available on SaaS platform, StreetLight InSight.
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As a Senior Machine Learning Engineer, you should be proficient in Data Structures, Java, object-oriented principles, building distributed systems, containerization, orchestration, and cloud-native architectures, you will collaborate with cross-functional teams to build scalable, reliable, and production-ready solutions.
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AI/Machine Learning Engineer, Manager Consultant. Bachelor's degree and 6-10 years of full-time working experience in AI, Data Science, and/or Machine Learning.
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Big Data/Machine Learning Engineer. Required Skills : SQL Tableau Reporting Python Data Analysis AWS. Look at customer data, gather, and produce monthly data analytics report.
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Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect.
$167,325 - $278,875 a yearFull-timeExpandApply NowActive JobUpdated 29 days ago - UpvoteDownvoteShare Job
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Collaborate with Data Science, Data Engineering, and Software Engineering teams to bring new metrics and techniques into the products. StreetLight pioneered the use of Big Data analytics to shed light on how people, goods, and services move, empowering smarter, data-driven transportation decisions.
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Shall create data science and data engineering products that include data models, data ingestion/transform, analytics which may include machine learning, and some form of output as either a machine-readable format (e.g. file output, database output, standard/streaming output) or a user interface or dashboard.
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Our data and storage solutions empower machine learning, artificial intelligence, cloud-based technologies, and other modern tools to create differential and scalable products. BS degree in Computer Science with 3-5+ years of experience as a software engineer with leadership exposure and experience mentoring junior engineers.
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We offer an array of services including Core Business Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud Adoption, Mobility, Digital Adoption, Agile & DevOps, Quality Assurance & Test Automation.
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