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Our team develops, implements, and maintains recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
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As a DevOps Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One. Senior Software Engineer, DevOps. Utilize programming languages like Java, Python, SQL, Ruby and Go, Container Orchestration services including Docker and Kubernetes, CM tools including Ansible and Terraform, and a variety of AWS tools and services.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Building machine learning models and systems, interpret their output, and communicate their results to internal/client teams and how those outcomes realize business value.
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Experience with DevOps processes and platforms such as GitHub, Terraform, Kubernetes, Helm, as well deployment in major cloud environments (AWS, Microsoft Azure, Google Cloud Platform) Ping is the collective sum of all our individual experiences, backgrounds and influences and we pride ourselves in growing and learning together.
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Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? Experience with data modeling, machine learning, data mining, statistics, or graph algorithms in academic or professional environments.
$250,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Solutions Architecture certification, such as AWS CSA or Azure Solutions Architect), Cloud Machine Learning certification, such as AWS Machine Learning, Azure Data Scientist Associate, or Databricks Certified Machine Learning Professional.
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Knowledge and hands-on experience with DevOps tool chain such as Git, Jenkins, Nexus, Docker, Kubernetes, Harness etc. Intimately familiar with Azure and AWS cloud technologies. Ability to operate and drive projects and results in a DevOps model collaborating with both Operations and Development to streamline the integration and deployment process.
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C#, developer, devops, sdet, software engineer, software programmer. · Cloud technologies: Containers (Docker/Podman), Public cloud (GCP/AWS), Microservices. c#, developer, devops, sdet, software engineer, software programmer.
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NET, C#, Visual Studio, Azure DevOps, JavaScript, HTML, SSRS, SSIS, and SQL. Experience working with Microsoft Visual Studio and Microsoft Azure DevOps. Troubleshoot issues and communicate progress and status on Azure DevOps work items.
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Our primary tech stack consists of Golang, Kubernetes, Postgres, and Elasticsearch, but we also use tools like ScyllaDB, Redis, Kafka, SQS, and various other AWS services as well. Required Experience: Experience with programming languages such as Go Lang, Python, or Java. Experience with Docker, Kubernetes, GraphQL, Postgres, Elasticsearch, ScyllaDB, Redis, Kafka, SQS, Docker, databases or AWS services.
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Ideal candidate has knowledge in: Containerization, Cluster Administration, CI/CD Deployments, IAC’ed Bootstrap and Deployment ● Experience with Machine Learning Engineering (MLE); worked on deploying machine learning models and applications to Kubernete ● 6+ years working with AWS constructs, at least one major serverless application architecture/deployment.
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That's why we need you, a Machine Learning (ML) Cloud and DevOps engineer, to help us shorten the time it takes to get critical tools developed and into the hands of our Agile developers creating AI products.
$123,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Develop and maintain data integration infrastructure: Design, develop, and optimize ETL processes using AWS Glue, Athena, Snowflake, DBT and other data engineering tools. You will leverage both SQL and Python-based approaches to work with native AWS data mesh technologies such as Glue and Athena, as well as Snowflake and DBT. You will work closely with a small, cohesive team, including software engineers and data scientists, to build a robust data platform that supports our mission to provide actionable insights for non-degree credentials.
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At least 8 years of organizational learning, facilitation and training experience working on complex international development programs, preferably in the sectors of agriculture, environment and/or food security.
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Professional trainings/certifications (AWS/Microsoft/Cyber Security/Agile/DevOps) strongly desired. Knowledge of emergent/innovative solutions in any of the following areas: Robotic Process Automation, Workflow Automation, Artificial Intelligence, Natural Language Processing, DevOps tools automation, Test Automation, Image Analysis, Auto-scaling Cloud Computing Architectures, Block Chain, Low-code/No-code solutions, Mirrored World BI, etc.
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machine learning aws devops jobs Title: engineer Company: Pri in Washington, DC
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