Machine Learning Engineer - MLOps

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Posted 2 days ago United States Salary undisclosed
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Job Description

Hi There, Hope yoursquore doing great, This is Nanda from Deegit Inc. I have an excellent job opportunity with one of our premier clients. Since it is an urgent business requirement your prompt response is appreciated. You can reach me at or mailto Title MLOps Consultant Location REMOTE As a MLOps engineer, you will work on AIML solutions, defining and implementing a tool chain to enable our internal team an efficient operation such as MLOps, containerization (Docker, Kubernetes) for a project critical to our customer needs Build and maintain tools and infrastructure for efficient software and AIML development Use MLflow tool to ndash o build and automate AIML workstream from data analysis, experimentation, operationalization, model training, model tuning to visualization o Increase our deployment speed, including the process for deploying models and data pipelines into production o manage on-prem deployments where compute is not on our cloud, but on customers' devicesprivate cloud Improve and maintain CICD pipelines and do manual deployments incase needed Build and maintain infrastructure as code in the cloud, that can scale when needed. Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation). Other responsibilities include documentation, hardware acquisition and regulatory compliance Idea candidate would have An experience of 3-4 years as DevOps or Cloud Engineer and atleast 1 year experience on automated deployment of ML models in production A B. Tech degree in CSE from a top engineering college Skills In-depth knowledge and experience using MLFlow or equivalent MLOps platform to manage complete ML lifecycle Hands-on experience with either of cloud services ndash AWSAzureGoogle Cloud Platform. Strong experience in scripting (Python, R, Scala) Experience with TensorFlow, Pytorch or other deep learning frameworks, regression techniques, and anomaly detection. Experience with DevOpsautomation tools such as GitLab, Ansible, Docker, Kubernetes, Jenkins Working knowledge of Multi-tier architectures load balancers, caching, web servers, application servers and databases. Hands-on software and hardware troubleshooting experience. Experience documenting and maintaining configuration and process information.