Machine Learning Engineer/AI Engineer

1. You will design, develop, test, deploy, maintain, and enhance Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions. 2. Participate and contribute to design reviews with platform engineering team to decide the design, technologies, project priorities, deadlines, and deliverables. 3. You will work closely with Data Lake and Data Science team to understand their data structure and machine learning algorithms. 4. Understanding of ETL pipelines, and ingress / egress methodologies and design patterns 5. Implement real time argo workflow pipelines, integrate pipelines with machine learning models, and translate data and model results into business stakeholders Data Lake 6. Develop distributed Machine Learning Pipeline for training & inferencing using Argo, Spark & AKS 7. Build highly scalable backend REST APIs to collect data from Data Lake and other use-cases / scenarios. 8. Deploy Application in Azure Kubernetes Service using GitLab CICD, Jenkins, Docker, Kubectl, Helm and Mainfest 9. Experience in branching, tagging and maintaining the versions across the different environments in GitLab. 10. Review code developed by other developers and provide a feedback to ensure best practices (e.g., checking code in, accuracy, testability, and efficiency) 11. Debug/track/resolve by analyzing the sources of issues and the impact on application, network, or service operations and quality. 12. Functional, benchmark & performance testing and tuning for the built workflows. 13. Assess, design & optimize the resources capacities (e.g .Memory, GPU etc.) for ML based resource intensive Required Skills : 1. Bachelor's/Master's degree in Computer Science or Data Science 2. 5 to 8 years of experience in software development and with data structures/algorithms 3. 5 to 7 years of experience with programming language Python or JAVA, database languages (e.g., SQL and no-sql) 4. 5 years of experience in developing large-scale infrastructure, distributed systems or networks, experience with compute technologies, storage architecture 5. Strong understanding of microservices architecture and experience with building and deploying RestAPI's using Python, Flask and Django 6. 5 years of experience with Unit and Functional test cases using PyTest, UnitTest and Mocking External Services for functional and non-functional requirements 7. Strong understanding and experience with Kubernetes for availability and scalability of the application in Azure Kubernetes Service 8. Experience in building and deploying applications with Azure, using third-party tools (e.g., Docker, Kubernetes and Terraform) 9. Experience with cloud tools like Azure and Google Cloud Platform 10. Experience with development tools, CI/CD pipelines such as GitLab CI/CD, Artifactory, Cloudbees and Jenkins Basic Qualification : Additional Skills : This contract has a high likelihood of extension and/or conversion/ Background Check :Yes Notes : Selling points for candidate :This contract has a high likelihood of extension and/or conversion/ Project Verification Info : Candidate must be your W2 Employee :Yes Exclusive to Apex :No Face to face interview required :No Candidate must be local :Yes Candidate must be authorized to work without sponsorship :Yes Interview times set : :No Type of project : Master Job Title :VMS Access Entry Branch Code :Portland