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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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Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities. Machine Learning:Supervised Learning: Techniques such as regression, decision trees, SVM, neural networks, etc.
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Experience and/or proficiency in Machine Learning, Artificial Intelligence, and/or Natural Language Processing. Experience developing and delivering technology in at least two of the following areas: data analytics, machine learning, data visualization, geospatial analysis, web services, or database development.
$96,000 - $144,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience and proficiency developing and implementing quality assurance and testing programs for workloads that are implemented with AWS services, and software development technologies that include Vue.js, Python, Django, S3, SNS, SQS, Docker, EKS/Kubernetes, AWS Step Functions, EventBridge, AWS Lambda, AWS API Gateway, Elasticsearch, Caching frameworks, like Redis, Memcached, the Amazon Relational Database Service (RDS) for Postgres, the MongoDB NoSQL database service, and other AWS services.
$87,100 - $130,700 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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Experience with provisioning virtual resources and building infrastructures in AWS, Google Cloud, Microsoft Azure, and Digital Ocean commercial clouds. Exposure to serverless provisioning such as AWS Lamda or Docker containers with Kubernetes.
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Conduct in-depth security assessments and audits of cloud environments, utilizing tools such as AWS Inspector, Azure Security Center, or Google Cloud Security Command Center. Collaborate with IT and cybersecurity teams to embed security into the DevOps pipeline, leveraging automation tools like Terraform, Ansible, or Chef for secure infrastructure provisioning.
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Knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Implement machine learning and artificial intelligence solutions to enhance predictive analysis and proactive issue resolution. Excellent understanding of at least 8 of the following - AWS EC2, Lambda, Beanstalk, ECS, CloudTrail, CloudWatch, Systems Manager, VPC, CloudFront, ALB, Neptune, RDS, Redshift, Aurora, Glue.
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Work with Technology Product Analysts and Scrum Master to ensure Project Backlog Items (PBIs) are documented and maintained in Azure DevOps (ADO) tool. Experience with e-learning development tools such as Oracle User Productivity Kit (UPK.
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Experience with designing, developing, deploying, or testing in Amazon Web Services ( AWS ) and using tools, including EC2, S3, ELBs, RDS, VPCs, security groups, Clou dTra il, CloudWatch, or IAM permissions.
$81,800 - $186,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Our client seeks a Machine Learning Engineer to provide data science and data engineering services, including developing data models, data ingestion/transformation, analytics, and machine learning.
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Experience developing applications/utilities using Python, Java, or Scala leveraging tools like Presto, AWS Athena, Spark or AWS Glue. Integrate solutions using an event driven architecture leveraging AWS GovCloud technologies.
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Demonstrated experience implementing machine learning models on text and multimedia data such as Spark NLP and Computer Vision models. Demonstrated experience using artificial intelligence and machine learning technologies/packages.
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Working knowledge of Microsoft Azure and Azure DevOps: Pipelines, Releases, Backlogs, Wiki. The ideal candidate will work as part of a collaborative team, communicate well, and is interested in continuous growth, learning and improvement.
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machine learning aws devops jobs Title: devops engineer Company: Pri in Fairfax, VA
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