| Cloud ML Engineer TX at Remote, Remote, USA |
| Email: [email protected] |
| From: Farha khan, Tek Inspirations LLC [email protected] Reply to: [email protected] Job Description - Cloud ML Engineer Hybrid Loaction: San Antonio, TX - 4 days onsite 1 remote in San Antonio, TX (candidate must live in San Antonio CURRENTLY) Need Local candidates of TX only Duration: 12+ months CANDIDATES MUST HAVE 10/10 ENGLISH I will call/email your candidate and CC you after the Spark Hire has been completed (I will send each of your candidates the link). The full job description and application steps are below. Position Summary: We are seeking a highly skilled ML Engineer with a strong background in Azure Cloud Engineering and Azure Machine Learning (AzureML) to join our team. The successful candidate will be responsible for designing, implementing, and maintaining our machine learning operations infrastructure within AzureML, ensuring efficient model development, deployment, and monitoring processes. Key Responsibilities: Monitor Azure Cloud resources, including AzureML environments and model performance, optimizing resource use and addressing issues to maintain high service reliability. Collaborate with data scientists, Hybrid Cloud, and DevOps for seamless ML model integration into production, ensuring scalability and reliability. Design, implement, and manage ML pipelines within AzureML for end-to-end automation of data processing, model training, validation, and deployment. Utilize AzureML for efficient scaling of ML models, applying best practices in version control, CI/CD, and lifecycle management. Manage CI/CD processes for machine learning models using Azure DevOps tools. Stay updated with the latest in Azure AI/ML features, applying best practices to leverage cloud-based AI/ML technologies effectively. Keep abreast of Azure advancements and best practices to enhance cloud-based AI/ML technology utilization. Must HaveQualifications: Proven (4+ 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. Familiar 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. Holds a Bachelors or Masters degree in Computer Science, Engineering, or related field, demonstrating a comprehensive understanding of both theoretical and applied aspects of machine learning and software engineering. Proven track record of successful AI/ML model deployments in Azure. Azure DP-100 Certification preferred. Keywords: continuous integration continuous deployment artificial intelligence machine learning Texas |
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| Wed Mar 13 03:08:00 UTC 2024 |