Lead Devops/ MLOps Engineer : Newtown Square PA/ Toronto ON : Onsite : C2H

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I have a job opportunity for you as Lead Devops / MLOps (Machine Learning Model Deployment Engineer) : Newtown Square PA / Toronto ON : Onsite : C2H I f you are interested share your resume ASAP.

Position : Lead Devops / MLOps (Machine Learning Model Deployment Engineer)

Location : Newtown Square PA / Toronto ON

Job Type : Contract to hire

100% Onsite (5 days onsite )

Job Description :

• 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
• Azure ML
• Linux / Shell 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)

Thanks & Regards

Shanti Yadav

Edge Global

1604 Spring Hill Road

Suite 221, Vienna, VA 22182

An E-Verified company

Sr. Technical Recruiter

Shanti@edgeglobal.net ,

703 436 4163 / 512 575 4263

linkedin.com / in / shanti-yadav-585394193

Edgeglobal LLC

www.edgeglobal.net

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