| Azure Machine Learning Architect || Locals in Santa Clara, CA. at Santa Clara, California, USA |
| Email: [email protected] |
| From: Ishavdeep Singh, Cloud Think Technologies [email protected] Reply to: [email protected] No Cpt/H1b Job Description: As an Azure Machine Learning Architect, you will play a pivotal role in designing, implementing, and optimizing machine learning solutions on the Azure platform. You will collaborate with data scientists, engineers, and stakeholders to architect scalable and efficient machine learning pipelines, models, and services. Your expertise in Azure ML services and best practices will contribute to the success of data-driven initiatives within the organization. Location: Santa Clara, California Responsibilities: 1. Solution Architecture: Design end-to-end machine learning solutions leveraging Azure ML services, considering factors such as scalability, performance, security, and cost efficiency. 2. Infrastructure Design: Architect cloud-based infrastructure and resources required for training, deploying, and managing machine learning models using Azure resources like Azure Databricks, Azure Kubernetes Service (AKS), Azure VMs, etc. 3. Model Development: Collaborate with data scientists to develop and deploy machine learning models using Azure ML pipelines, ensuring best practices for model versioning, tracking, and reproducibility. 4. Data Integration: Integrate diverse data sources and preprocess data for training and inference, using Azure Data Factory, Azure Data Lake, or other relevant Azure services. 5. Deployment and Monitoring: Deploy models to production environments using Azure ML deployment technologies like Azure ML Service, Azure Functions, or AKS, and establish monitoring mechanisms for model performance, drift, and health. 6. Security and Compliance: Implement security measures, access controls, and data protection protocols in accordance with organizational policies and regulatory requirements. 7. Optimization: Continuously optimize machine learning pipelines and models for performance, cost, and resource utilization using techniques like distributed computing and model quantization. 8. Documentation: Create technical documentation, architecture diagrams, and guidelines for the development team and stakeholders. 9. Collaboration: Collaborate with cross-functional teams including data scientists, software engineers, DevOps, and business stakeholders to align machine learning initiatives with business objectives. Qualifications and Skills: - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. - Proven experience in designing and architecting machine learning solutions on the Azure platform. - In-depth knowledge of Azure ML services, Azure Databricks, AKS, Azure Data Factory, and other relevant Azure services. - Proficiency in programming languages such as Python or R, and experience with machine learning libraries/frameworks like TensorFlow, PyTorch, or scikit-learn. - Strong understanding of machine learning principles, data preprocessing, and feature engineering. - Familiarity with containerization technologies (Docker) and orchestration tools (Kubernetes). - Excellent problem-solving and communication skills. - Experience with DevOps practices and CI/CD pipelines for machine learning models is a plus. - Relevant Azure certifications (such as Azure AI Engineer or Azure Data Scientist) are advantageous. Keywords: continuous integration continuous deployment artificial intelligence machine learning rlang |
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| Tue Aug 29 20:56:00 UTC 2023 |