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Relevant certifications (e.g., AWS Certified DevOps Engineer, Azure DevOps Engineer Expert, Certified Kubernetes Administrator) are a plus. Proven experience with LoadRunner, Selenium, Docker, Kubernetes, Jenkins, Azure DevOps, Veracode, MSFT Power Platform, MSFT Power Automate, and cloud platforms (Azure/AWS.
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Lead Software Engineer, DevOps. New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Software Engineer. Lead a portfolio of diverse technology projects and a team of developers with deep experience in machine learning, distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.
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Strong knowledge of configuration management software such as Power Shell, Tera form, Ansible, Continuous integration tools such as Azure DevOps, Jenkins. Engineers in the group can be found wearing any number of hats: from software engineer, reliability engineer to developer advocate and evangelist.
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5+ years of experience in a DevOps role or a related field Proven experience as a Cloud Operations Engineer or a similar role, with a focus on Microsoft Azure, Kubernetes, Micro Services, Office 365, and Citrix Cloud Proven experience with Microsoft Azure, including IaaS, PaaS, and SaaS offerings Experience with SDLC and rich experience with Deployment pipeline and release, Agile methodologies.
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Job Description :We are looking for a seasoned Machine Learning Engineer specialized in Large Language Models (LLMs) to drive the development and deployment of cutting-edge AI solutions.
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Minimum 5 years’ experience in data engineering with a proven track record in the Azure ecosystem and with Azure DevOps. Minimum 5 years’ experience with Data Modeling, ETL, and Data WarehousingMinimum 3 years’ hands on experience with Azure Services.
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Our provides end-to-end lifecycle support for Navy Reserve business systems, including full-stack web/mobile-responsive development, SharePoint knowledge management and development, machine learning, date warehouse administration, desktop/server administration, networking, and AWS cloud infrastructure support.
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Familiarity with enterprise technology tools: Tidal Enterprise Scheduler, Service Now, JIRA, Confluence, Azure DevOps, Azure GIT. The team works closely with front office groups and the technology teams that support them, including but not limited to Operational and Investment Risk, Institutional Equities & MAC investment teams, Fixed Income, Equity Research, and Wealth Management across the firm’s global offices.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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Expert in creating CI pipelines using Jenkins, AWS and Azure DevOps. Experienced in Cloud Testing using Azure DevOps and AWS. 2+ years working as Test Automation Test Engineer (or similar), including proven experience of designing and implementing Automation Testing frameworks and methodology to support agile product development.
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Job Summary: As a Director, Software Engineering you will be responsible for leading a group of engineering managers and their respective engineering squads within the Identity Engineering organization.
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Job DescriptionGen AI Solution Architect/Delivery Lead -DescriptionJob Title: Databricks Generative AI Solution Architect / Delivery LeadJob Location: Hybrid (preferred base cities: Atlanta, NYC, Chicago, NYC, Dallas, Houston, and Seattle)Job description: The AI Architect will leverage expertise in data science, specifically in artificial intelligence, machine learning, and software architecture to address complex business challenges.
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Track record of successful product development and deployment using modern software engineering, DevOps, Agile, SCRUM and sprint practices, Azure or AWS, and Docker or Kubernetes.
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Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
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