Current jobs related to Azure MLOps Engineer - Teaneck, New Jersey - BEHAVIORALLY INC

We are seeking a skilled Azure MLOps Engineer who excels in a dynamic and innovative technology landscape, focusing on the implementation of top-tier DevOps and MLOps methodologies.

Essential Qualifications:

• A minimum of 5 years of practical experience in DevOps within the Microsoft Azure Cloud, emphasizing MLOps, including:
  • Networking: Proficiency with Azure Load Balancer and Azure Application Gateway.
  • Compute: Experience with Azure Functions.
  • Monitoring: Familiarity with Azure Monitor.
  • Container Orchestration: Knowledge of Kubernetes.
  • IaaC: Expertise in ARM templates.
  • MLOps: Experience with Azure ML and ML Flow.
• Proven track record in integrating solutions with Microservices, RESTful Web Services, and Web APIs.
• Strong grasp of CI/CD pipelines, with experience using tools such as Jenkins, Git, and Docker.
• In-depth understanding of computer vision techniques, including Convolutional Neural Networks (CNN), object detection, and image segmentation.
• Demonstrated experience in developing and deploying machine learning models, particularly in computer vision.
• Proficient in SQL and familiar with any RDBMS and PowerBI.
• Ability to work collaboratively and communicate effectively in a team-oriented environment.

Preferred Qualifications:

• Relevant certifications in AI/ML technologies and Azure, such as Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect.

Key Responsibilities:

• Collaborate with product teams to create scalable and efficient solutions, ensuring alignment with architectural best practices and business objectives.
• Assist in the development and refinement of machine learning algorithms and models, offering guidance on best practices and methodologies.
• Support the design and execution of data pipelines for data ingestion, processing, and feature engineering, ensuring data quality and integrity.
• Design, implement, and manage robust Continuous Integration and Continuous Deployment (CI/CD) pipelines for machine learning models and applications, collaborating with cross-functional teams to enhance CI/CD best practices.
• Utilize expertise in Azure to architect and deploy machine learning solutions within the Azure ecosystem, managing and optimizing Azure-based infrastructure for security, scalability, reliability, and performance.
• Implement and oversee deployment strategies for machine learning models in both development and production environments, working closely with data scientists and engineers to streamline deployment processes and monitor model performance.
• Develop comprehensive testing protocols for machine learning models, ensuring thorough evaluation and validation across various environments. Implement automated testing procedures to ensure the reliability and accuracy of deployed models, and develop monitoring solutions to maintain the health and performance of these models.
• Work collaboratively with data scientists, software engineers, and other stakeholders to understand requirements and integrate machine learning models into the overall system. Maintain detailed documentation for CI/CD pipelines, deployment processes, and infrastructure configurations.