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Experience with Containers and Container orchestration Kubernetes platforms such as PODMAN, docker, EE/OpenShift/Rancher. Experience with script languages such as Groovy, Python, Shell, Ruby, bash, shell, Perl.
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Experience or familiarity with one or more of the following technologies: PHP, Kotlin, Scala, Python, Java, Node.js , React, MySQL, Kafka, Docker, Kubernetes, Terraform, AWS, Elasticsearch, XCUITest, Selenium, JUnit, NUnit, Espresso.
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Knowledge on GraphDB (Neo4j, ArrangoDB, JanusGraph, Neptune) MongoDB, Python/Django, data structure and algorithms would be added advantage. Exposure to Linux, EC2 Security, EC2 Balances, Automation Tools, AWS CLI,S3, Cloud Watch & Cloud Trail, SSH, Docker, Git, MLAB, Jenkins, Circle CI, Nagios, Jmeter & Blazemeter are must.
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Kafka, Docker, Jenkins, Spinnaker, SRE. Extensive experience of using CI-CD tools like GIT, Docker, Jenkins, Ansible, Spinnaker etc. Proficiency with docker deployments using Kubernetes.
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Our tech stack includes Neo4J, Postgres, ElasticSearch, Redis, RabbitMQ, Docker, Kubernetes, NextJS, and BlitzJS. We work primarily in Typescript and Python. Experienced and comfortable in Python, Javascript/Typescript.
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Server: Python, Go, AWS, Kubernetes, Docker, Prometheus, MongoDB, Redis, Elasticsearch, DynamoDB. You have knowledge of AWS, Kubernetes, and Docker, or other similar infrastructure platforms and tools.
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Spring boot, Microservices, Docker, Jenkins and REST API's experience. Knowledge of Statistics, SAS, Python, Computer Vision, data visualization tools. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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PREFERRED EXPERIENCE: Experience with GPU kernel programming using CUDA, HIP or OpenCL. Experience in Python Experience in implementing and optimizing parallel methods on GPU accelerators (NCCL/RCCL, OpenMP, MPI) Performance analysis skills for both CPU and GPU Experience with Singularity, Docker, and/or Kubernetes.
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DevOps: Azure DevOps, Docker, Kubernetes. Languages: JavaScript, Python, C#, SQL, Terraform. DevOps: Azure DevOps, Docker, Kubernetes. Retrieval-Augmented Generation (RAG): Experienced in implementing the RAG pattern to augment chat responses with information retrieved from Azure Cognitive Search, enhancing the accuracy and relevance of chatbot replies.
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Containers and related technologies (Docker, Kubernetes, AWS ECS, etc.) Must have expertise in some of the following: Python 3 RDBMS (PostgreSQL, SQL Server, Oracle, DB2, etc.) being proficient with SQL SQL query and performance tuning Amazon RedshiftExperience with some of the following is a huge bonus: Amazon EMR Apache Spark Scala Git (or other modern source control) Runtime Configuration Management (e.g. 12 Factor Apps) Continuous Build Systems (Jenkins, Bamboo, etc.
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Position is local to ATX. 2+years of experience Python proficiency is required Experience designing RESTful or GraphQL APIs Comfortable with AWS/GCP/or Azure Comfortable with deep learning libraries Docker / Kubernetes Kofi Group places software engineers and machine learning engineers on a direct-hire basis with VC-backed startups in San Francisco/Silicon Valley, New York, and Austin.
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Knowledge and experience in working with Docker, Kubernetes, and related technologies. 3+ years of professional experience with the Python programming language. Primary skill : Python and DevOPs.
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Proficiency in SQL, Python and working with Data Science tools (e.g., git, kubernetes, Docker, etc. Experience with data visualization (preferably Looker). Proficiency in SQL, Python and working with Data Science tools (e.g., git, kubernetes, Docker, etc.
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Experience with containers and container orchestration platforms such as Docker, Kubernetes or equivalent. Passionate about operational excellence through proper automation and engineering processes using programming languages such as Go, Python, Java, or other JVM languagesProficient in working with Linux or other POSIX operating systems, shell scripting, and networking technologies.
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Devops tools and deployment pipelines - Jenkins, udeploy, ansible, chef, docker, Kubernetes. Familiarity with Docker/Kubernetes and container-based development and deployment practices will be a plus.
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