| MLOPS Architect at Remote, Remote, USA |
| Email: [email protected] |
| From: Swati Nishad, Inherent Technologies [email protected] Reply to: [email protected] Position: MLOPS Architect Location: Remote Duration: 1 Years Phone & Skype Client: HCL Immediate Interview JD: - overall Experience of 12-15 Yrs Experience supporting machine learning projects. - Expert with ML platforms (e.g., TensorFlow, PyTorch). - Experience with cloud platforms (e.g. Azure). - Bachelor's degree in Computer Science, Engineering, or a related field. - Proven experience as a Data Engineer or in a similar role. - Experience with big data tools (e.g., Hadoop, Spark) and databases (e.g., SQL, NoSQL). - Knowledge of machine learning concepts and workflows. - Strong programming skills (e.g., Python, Java). - Excellent problem-solving abilities and attention to detail. - Strong communication skills to effectively collaborate with other teams. Design and optimize pipelines for model deployments in production environments using containers (Docker or Azure Kubernetes), Azure DevOps and/or MLOps and Azure Data Factory. Knowledge of Azure Databricks pipeline and ML Model deployment is mandatory. Implement efficient microservices frameworks i.e. API Management, message broker, load balancing, etc Troubleshoot, improve, and scale continuous integration, continuous delivery, and continuous deployment (CI/CD) pipelines Write design documents to build consensus for new systems components and enhancements to existing components Extensive programming experience in Python and/or R with knowledge of Object-Oriented Programming. Experience in Azure DevOps & Azure Cloud Services (e.g. Azure Blob, Azure Key Vault, Azure Data Factory) or similar experience with AWS or Google Experience with CI/CD pipelines, Automated Testing, Automated Deployments, Agile methodologies, Unit Testing and Integration Testing tools Demonstrated history of designing solution pipelines from conception to deployment in production environments e.g. Docker containers on Kubernetes-based platforms with data orchestration in Azure Data Factory Nice to Have: Knowledge of JFrog Artifactory is a plus. Experience with front-end user interface development using various HTML-related tool frameworks like Django, FastAPI (Python), Java/Javascript etc Experience with in memory and/or distributed computing frameworks (e.g. Spark, Hadoop) Conduct performance testing on API endpoints and batch jobs to identify and correct CPU and memory bottlenecks Skill Mandatory Proficiency Level (1-5) Azure DevOps CI/CD Y 4,5 Azure Cloud Engineer Y 4, 5 Databricks Pipelines Y 3,4 Familiarity with ML platforms (e.g., TensorFlow, PyTorch) & MLOPS Y 3 Azure ML N 3,4 Knowledge of JFrog Artifactory N 2,3 (Good to have) Keywords: continuous integration continuous deployment machine learning rlang MLOPS Architect [email protected] |
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| Thu Sep 26 20:13:00 UTC 2024 |