Machine Learning Engineer

3 weeks ago


Irving, United States EITACIES Full time

About US : Since 2008, EITACIES has been a beacon of innovation, crafting tailored tech solutions. From humble beginnings, we've grown globally, nurturing client relationships and adapting to digital shifts. Today, we're a tech powerhouse, delivering customized excellence from startups to Fortune 500, State & Federal clients.Job Description10+ Years of ExperienceStrong resource on AWS Cloud Ops and Kubernetes ClustersThis is a fundamental team in our AI Center, and RTML Framework serves all of our real time AI models in the production - enabling our business organizations to maximize the benefits of using AI-driven solutions for our customers.Working closely with other teams to define technical strategy, architecture, development choices and ensure overall growth of the Jarvis Framework to meet our internal customers' needs.Leading the Jarvis development activities through phased releases, ensuring it is architecturally sound, implemented correctly/efficiently, and delivered on time.RequirementBachelor's degree or above in Computer Science/Engineering or other related areas.At least two years are in AI / ML Engineering areas with reasonably good understanding of Data Science and AIML practices/workflows.Strong expertise in RTML model serving arena and/or large scale cloud-based RT framework development.Experience with Kubernetes, comfortable with kubectl and helm.Experience in creating, deploying, and maintaining centralized KubeFlow infrastructure on top of one or multiple kubernetes clustersExperience with cloud infrastructures and MLOps in clouds.Familiar with CI/CD process and common frameworks such as ArgoCD.Experience with programming languages such as Python and Java.Experience in large application development in cloud environments - AWS, Google Cloud Platform and On-Prem clusters.Experience in K8s architecture and principle of operations, hands-on skills of deploying large applications in production K8s cluster, configuring K8s properly, and troubleshooting when the application has issues.Good understanding of of RT system stats collection and performance monitoring methodsBasic understanding of RT Feature Engineering methodology and practicesUnderstand basic data science concepts and common needs from data scientists.Regards,Karthika SMachine Learning Engineer#J-18808-Ljbffr

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