100% remote
No C2C candidates will be considered
Top 5-10 responsibilities for this position……
o You will design, develop, test, deploy, maintain, and enhance Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions.
o Participate and contribute in design reviews with platform engineering team to decide the design, technologies, project priorities, deadlines, and deliverables.
o You will work closely with Data Lake and Data Science team to understand their data structure and machine learning algorithms.
o Understanding of ETL pipelines, and ingress / egress methodologies and design patterns.
o Implement real time argo workflow pipelines, integrate pipelines with machine learning models, and translate data and model results into business stakeholders Data Lake.
o Develop distributed Machine Learning Pipeline for training & inferencing using Argo, Spark & AKS.
o Build highly scalable backend REST APIs to collect data from Data Lake and other use-cases / scenarios.
o Deploy Application in Azure Kubernetes Service using GitLab CICD, Jenkins, Docker, Kubectl, Helm and Mainfest.
o Experience in branching, tagging and maintaining the versions across the different environments in GitLab.
o Review code developed by other developers and provide feedback to ensure best practices (e.g., checking code in, accuracy, testability, and efficiency).
o Debug/track/resolve by analyzing the sources of issues and the impact on application, network, or service operations and quality.
o Functional, benchmark & performance testing and tuning for the built workflows.
o Assess, design & optimize the resources capacities (e.g .Memory, GPU etc.) for Client based resource intensive workloads.
Skills/technologies are required
o Bachelor’s/Master’s degree in Computer Science or Data Science.
o 5 to 8 years of experience in software development and with data structures/algorithms.
o 5 to 7 years of experience with programming language Python or JAVA, database languages (e.g., SQL), and no-sql.
o 5 years of experience in developing large-scale infrastructure, distributed systems or networks, experience with compute technologies, storage architecture.
o Strong understanding of microservices architecture and experience with building and deploying RestAPI’s using Python, Flask and Django.
o 5 years of experience with Unit and Functional test cases using PyTest, UnitTest and Mocking External Services for functional and non-functional requirements.
o Strong understanding and experience with Kubernetes for availability and scalability of the application in Azure Kubernetes Service.
o Experience in building and deploying applications with Azure, using third-party tools(e.g., Docker, Kubernetes and Terraform).
o Experience with cloud tools like Azure and Google Cloud Platform.
o Experience with development tools, CI/CD pipelines such as GitLab CI/CD, Artifactory, Cloudbees and Jenkins.
Skills/attributes are preferred
o Python, Kubernets, Argo Workflow, Argo Event, Hive, SQL, no-sql, RestAPI’s, Helm, Docker, Jenkins.
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No C2C candidates will be considered
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