| Lead Devops/ MLOps Engineer||Newtown Square PA (Onsite) at Remote, Remote, USA |
| Email: [email protected] |
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http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=2089682&uid= Title : Lead Devops/ MLOps Engineer (Machine Learning Model Deployment Engineer Location: Newtown Square PA (Onsite) Local Only Duration: Long Term Visa: No OPT & CPT Seeking for skilled and detail-oriented Machine Learning Model Deployment Engineer to manage, streamline and optimize the deployment of Machine Learning models using Docker, AKS. Hands On experience in DevOps and MLOps practices, with a focus on managing cloud-based machine learning environments. Model Deployment Build, optimize, and maintain cloud-based environments for deploying, monitoring, and scaling machine learning models and data pipelines. Package machine learning models into Docker containers (Relative experience in ML models) Solid foundational knowledge of Azure Open AI and GPT LLM model fine-tuning techniques, with a strong grasp of prompt engineering principles. Develop and automate the unified CI/CD pipelines in Azure DevOps Hands-on experience in containerization and orchestration tools such as Docker and AKS Work closely with data scientists to ensure smooth handoffs and integration of machine learning models into production systems. Automate model testing, validation, and performance monitoring for containerized solutions. Deploy and manage code using Azure Repos, and Azure DevOps (CI/CD, Docker, Function Apps), and utilize Kubernetes Helm charts for model deployment. Implement Docker best practices. Design and implemented a complete MLOps pipeline utilizing Azure Machine Learning in conjunction with open-source frameworks Dockerize ML model training and serving processes, containerizing them according to specific versions, and then deployed the containers to an Azure Kubernetes environment. Contribute to the establishment of a unified CI pipeline, facilitating the efficient use, synchronization, and application of common templates and files across downstream repositories using Copier and Azure Repos. Enforce best coding practices within the MLOps pipeline, including linting, unit testing, and version validation. Set up and deploy the MLflow stack for model experiment tracking, version management, and registry. Implement Docker best practices, optimizing Dockerfile and Docker Compose to minimize Docker image size. Configure data drift, target drift, and data quality metrics with Evidently and developed a user-friendly web app for easy drift detection between training and production data. Work closely with the cross-functional team including data science team, engineers etc. Experience in AKS Cluster setup. Experience in cloud-native tools for monitoring containerized application, auto-scaling and load balancing. Strong understanding on machine learning lifecycle and model integrations. Tools and techniques to have hands-on experience. Python Machine Learning Frameworks Docker AKS Azure ML Linux/ scripting Data and Model Drift monitoring (EvidentlyAI) Kubeflow Azure DevOps, AutoML MLFlow Strong problem and debugging skills. Handle Deployment challenges. Ability to quickly learn on the new open-source tools. Good experience in Cost Analysis on the tools (Docker, AKS, ACR etc.) Ensure compliance with organization and regulatory requirements (Security and Compliance) Best Regards, Amit Vikal | Talent Acquisition Specialist Metrix IT Solutions INC 8832 Blakeney Professional Dr, Ste 205, Charlotte, North Carolina 28277 D: 980-737-1626 [email protected] -- Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology Pennsylvania Lead Devops/ MLOps Engineer||Newtown Square PA (Onsite) [email protected] http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=2089682&uid= |
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| 07:31 PM 17-Jan-25 |