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New York City (Hybrid On-Site): $165,100 - $188,500 for 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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Proven prior experience as a Machine Learning Engineer, Data Engineer, Software Engineer, or similar role. We are seeking an experienced Machine Learning Engineer (MLE) Manager to join our team.
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We develop cutting edge sensors and mission systems, high bandwidth communication systems, large-scale simulation systems, space and satellite systems, avionics virtual machines as part of high fidelity digital twins that will improve the future of software development, airplane and flight controls, cyber security solutions, artificial intelligence, machine learning, and much more.
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Comprehensive technical expertise and a research track record in one or more of the following domains: artificial intelligence/machine learning; advanced cybersecurity methods and technologies; computer science and engineering; software engineering; modeling and simulation; model-based systems engineering; and/or computational science and engineering.
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The ideal candidate will have experience in some or all the following: Machine learning, Robotics Operating System (ROS), light detection and ranging (LiDAR), computer vision, simultaneous localization and mapping (SLAM.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. Experience with DevSecOps , CI and CD, IaC and CaC, IT Infrastructure Library, and IT Service Management.
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We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
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Your technical expertise will be vital as you help customers overcome their most difficult challenges by leading Cybersecurity technologies and domains, including IoT and Cloud security, Automation and Orchestration (A&O), identify and access management, and machine learning.
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Opportunities exist to support faculty and student technology needs on intriguing research projects in the areas of robotics, artificial intelligence/machine learning, combustible engines, electric motors, nanoscale devices, fresh water, imaging/visualization, materials/structural testing, and human performance/biomedical engineering.
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Experience working on PySpark (the Python API for Spark), the Databricks Machine Learning Runtime, and other popular machine learning libraries like TensorFlow and scikit-learn.
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Mit dem Machine Learning Incubator bietet das Unternehmen ein Programm zur Ausbildung der nächsten Generation von Entscheidungsträgern, Data Scientists und Entwicklern an. Machine Learning Reply befähigt seine Kunden, neue datenbasierte Geschäftsmodelle erfolgreich einzuführen sowie bereits bestehende Prozesse und Produkte zu optimieren – mit einem Schwerpunkt auf Open-Source- und Cloud-Technologien.
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Familiarity with artificial intelligence, machine learning, and/or deep learning and supporting tooling. Find even more open roles in Ethical Hacking, Pen Testing, Security Engineering, Threat Research, Vulnerability Management, Cryptography, Digital Forensics and Cyber Security in general - ordered by popularity of job title or skills, toolset and products used - below.
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To enable this, The Aerospace Corporation is focusing on critical technologies such as artificial intelligence, machine learning, photonics, optical communications, additive manufacturing, electric propulsion, as well as new tools in modeling, simulation, cloud.
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Work closely with the Technical Lead and Director, ML/AI in all aspects of data, like Connect and automate the pipelines, data processing through streaming cluster, provide data as products building data lake, data warehouse and data mart, and data cleansing and data governance developing big data engineering, Machine Learning and advanced analytics solutions.
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And we’re pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence. And we’re pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence.
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