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Proven experience (3+ years) as a Machine Learning Operations Engineer with a focus on NVIDIA Triton. Knowledge of DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines Familiarity with the AWS cloud platform Previous experience in the deployment of machine learning models in production environments.
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We are seeking highly skilled and motivated Senior and Principal Research Scientists to join our team working on cutting-edge projects within the domains of Radio Frequency Machine Learning (RFML), Digital Signal Processing (DSP), and/or Software Defined Radio (SDR.
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Experience with RESTful services, JavaScript, Bash scripting, Jenkins, Rancher/Kubernetes, Docker, Airflow, and data science/machine learning are preferred. - Strong proficiency in Python, Splunk, GitLab, and Atlassian Jira. - Proven expertise in cybersecurity principles and practices.
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Desired: Cloud System Administration Certification (AWS or other cloud platform), Ansible automation, Experience working in an Agile and Scrum environment, Machine Shop Administration (NSA proprietary), Experience using Kibana or Splunk dashboards to monitor application activity, Risk Management Framework, Docker or Kubernetes containerization experience.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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We are committed to developing exceptional talent and fostering a culture of innovation, and strive to foster an environment that welcomes a diversity of backgrounds and professional experience as we make advances in machine learning and artificial intelligence.
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Experience with a ticketing system such as BMC Remedy and/or Atlassian JIRA. Experience with a ticketing system such as BMC Remedy and/or Atlassian JIRA. Experience supporting, installing and configuring enclave Fiber/Ethernet switches, HPE storage area networks (SAN)/ network attached storage (NAS.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. Experience with DevSecOps, CI/CD, IaC and CaC, IT Infrastructure Library, and IT Service Management.
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Working knowledge of product management tools, like Jira, Confluence, Azure DevOps required. SENIOR PRODUCT MANAGER HEALTHCARE INDUSTRY AND BUSINESS SKILLS Understanding of the healthcare industry, including an advanced understanding of healthcare workflows, purchaser types, user needs, funding mechanisms, and industry challenges.
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Net, C#, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Python, Data Modeling, SQL, SSIS, SSAS, SSRS, Power Automate, Power Platform, AI Builder, Power Apps, Blue Prism, Automation Anywhere, UiPath Studio, Orchestrator, ERP, QuickBooks, SAP, NetSuite, Oracle, API, JSON, XML, Web Services, SOAP, Postman, Fiddler, Integration, Custom Activities, DLL, Insight, Automation Hub, Task Capture.
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We specialize in Computer Network Operations (CNO), embedded development, software engineering, cloud engineering, Artificial Intelligence and Machine Learning (AI/ML), DevOps support, systems engineering and more.
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Basic understanding of machine learning, natural language processing, and vector database concepts. Interested in learning more about Visionist and the work we do? Proficiency in JavaScript and experience with modern web development frameworks (e.g., React, Vue.js.
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The candidate will apply advanced machine learning methods, utilizing remote sensing data from NASA and other agencies, and commercial platforms, to support the development of integrated water cycle modeling tools in an open science environment.
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GliaCell’s Enterprise capabilities include Full-Stack Application Development, Big Data, Cloud Technologies, Analytics, Machine Learning, AI, and DevOps Containerization. GliaCell is seeking a Junior Software Engineer on one of our subcontracts.
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Act as an administrator for commercial off the shelf software (ex: JIRA) used by customers in their Agile planning, configuration, testing, deployment and execution of DevSecOps pipelines within the platform.
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