| Azure MLOPS Engineer - Must sit in San Antonio, TX (4 days onsite, 1 day remote) - 10+ years local candidates only at Remote, Remote, USA |
| Email: [email protected] |
| Hiring: Azure MLOPS Engineer - Must sit in San Antonio, TX (4 days onsite, 1 day remote) - 10+ years local candidates only Hi Partners, Please Check the JD below and let me know if you have anyone on bench. No USC/GC/GC-EAD on C2C. 10+ years experience is required. If you have anyone, please send me their resume with the details below. If any details are missing, there will be a delay in response. Full Name: Visa: Complete DOB: LinkedIn: 10+ years local candidates only Role: Azure MLOPS Engineer Location - Must sit in San Antonio, TX (4 days onsite, 1 day remote) Local Candidates only Contract 12+ Month Required Skills: Azure Cloud Azure Machine Learning (AzureML) Azure AI Platform Azure DevOps (ADO) Python Additional Skills: Azure DP-100 Certification ADLS Azure Synapse Qualifications To be successful in this role, you will ideally possess the following qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field, demonstrating a comprehensive understanding of both theoretical and applied aspects of cloud engineering/infrastructure. Proven (3+ years) experience in Azure Cloud engineering with a strong focus on AzureML, including managing ML workflows. Expertise in Python for AI/ML workflows, proficient with additional scripting languages (e.g., Bash, PowerShell). Familiarity with Azure DevOps (ADO), CI/CD practices, and Azure AI/ML services. Strong foundation in AI/ML principles, with practical experience in deploying models at scale. Proven track record of successful AI/ML model deployments in Azure. Azure DP-100 Certification preferred. Join our cutting-edge Data Science & AI team and contribute to the future of AI/ML technology! In this role, you'll leverage Azure to drive innovation and operational excellence in our AI/ML initiatives. Here's what you can expect: Be at the forefront of AI/ML advancements, applying your skills to solve real-world problems. Collaborate with a talented team of Data Scientists, ML Engineers, and cloud experts. Work in a fast-paced environment that fosters continuous learning and growth. Make a significant impact on the company's success through the power of AI/ML. Key Responsibilities As an Azure Cloud Engineer on our Data Science & AI team, you will play a critical role in designing, implementing, and maintaining our AI/ML environment within Azure. You'll collaborate closely with Data Scientists, Hybrid Cloud, and DevOps engineers to ensure a seamless transition of ML models from development to production. Here's a breakdown of your key responsibilities: Azure Cloud Management: Manage and maintain the Microsoft Azure cloud infrastructure, services, and solutions relevant to AI/ML operations. Use Microsoft Infrastructure as Code (IaC) and Terraform pipelines for deploying Azure resources. Monitor Azure Cloud resources, including Azure AI services, AzureML environments, and model performance, optimizing resource use and addressing issues to maintain high service reliability. Machine Learning Operations (MLOps): Design, implement, and manage end-to-end ML pipelines within AzureML for data processing, model training, validation, and deployment. Utilize AzureML for efficient scaling of ML models, applying best practices in version control, CI/CD (using Azure DevOps tools), and lifecycle management. Collaboration and Integration: Collaborate with Data Scientists, ML Engineers, Hybrid Cloud, and DevOps engineers to ensure seamless integration of AI/ML models into production, focusing on scalability and reliability. Additional Skills:Stay updated with the latest advancements in Azure AI/ML features and best practices to leverage cloud-based AI/ML technologies effectively. Thanks Aayushi Senior Technical Recruiter/Lead | Empower Professionals [email protected] Nishant Sharma Empower Professionals [email protected] Aayushi Verma 100 Franklin Square Drive Suite 104, Somerset, NJ 08873 Keywords: continuous integration continuous deployment artificial intelligence machine learning green card New Jersey Texas Azure MLOPS Engineer - Must sit in San Antonio, TX (4 days onsite, 1 day remote) - 10+ years local candidates only [email protected] |
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| Tue Oct 29 22:52:00 UTC 2024 |