Job
Description
Position Overview: We are seeking a highly skilled Technology/Solution Architect with extensive experience in large-scale data processing, image storage and processing, and deep learning (DL) and machine learning (ML) model training and evaluation. The ideal candidate will have a strong background in Azure infrastructure and a comprehensive understanding of data engineering and MLOps practices. Key Responsibilities: Design and architect scalable solutions for storing, retrieving, and processing large image datasets. Lead the preprocessing, augmentation, and annotation of image data for various projects. Utilize Azure infrastructure, including Azure Blob Storage, Azure Data Lake, Azure Databricks, Azure Machine Learning, and Azure Synapse Analytics, for data processing and model training. Deploy and manage edge servers and edge modules using Azure IoT Hub. Implement and manage Docker containers for various applications. Collaborate with data scientists and engineers to support DL/ML model training, evaluation, and deployment. Apply advanced MLOps practices to streamline model deployment, monitoring, and lifecycle management. Provide technical leadership and guidance on best practices for data engineering, image processing, and model training. Required Skills: Proficiency in Python for data processing, automation tasks, and model development. Extensive experience with Azure services, particularly Azure Blob Storage, Azure Data Lake, Azure Databricks, Azure Machine Learning, and Azure Synapse Analytics. Strong knowledge of Docker and edge server management. Expertise in large-scale data processing techniques. Proficiency in OpenCV for image processing tasks. Advanced knowledge of MLOps practices and tools. Strong understanding of DL/ML model training, evaluation, and deployment. Preferred Skills: Experience in designing and implementing scalable data architectures. Familiarity with data augmentation and annotation techniques. Proven track record of leading technical teams and projects. Strong problem-solving skills and attention to detail. Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience in technology or solution architecture, with a focus on data engineering and ML/DL. Strong leadership and communication skills.
