Urgent Req "Mlops Architect"

Hi ,

Hope you are doing great today! Let me know if you are interested in the below position.

Role : Mlops Architect

Location : Dallas TX/Charlotte NC/Atlanta GA/Remote

Job Summary:

As an MLOps Architect, you will be responsible for designing, implementing, and maintaining the infrastructure and tools necessary to support the end-to-end machine learning lifecycle. Your primary focus will be on deploying MLOps solutions using AWS SageMaker, ensuring the robustness, scalability, and reliability of our machine learning workflows.

Key Responsibilities:

Architecture & Design:

Design and implement MLOps architecture to support the development, deployment, and monitoring of machine learning models.

Develop scalable, high-performance cloud infrastructure using AWS SageMaker and other AWS services.

Ensure best practices in version control, CI/CD pipelines, and automation for machine learning models.

Deployment & Automation:

Implement and manage automated workflows for model training, validation, deployment, and monitoring.

Set up and manage model versioning and rollback mechanisms.

Develop scripts and tools to automate data preprocessing, model training, and deployment processes.

Monitoring & Maintenance:

• Monitor model performance and health in production, identifying and addressing issues proactively.
• Implement and maintain monitoring and alerting systems to ensure high availability and performance.
• Conduct regular reviews and optimizations of deployed models and infrastructure.
• Collaboration & Communication
• Work closely with data scientists, data engineers, and DevOps teams to integrate machine learning solutions into existing systems.
• Provide guidance and support to teams on MLOps best practices and methodologies.
• Communicate complex technical concepts to non-technical stakeholders effectively.

Documentation & Reporting:

• Maintain comprehensive documentation of MLOps processes, tools, and systems.
• Generate regular reports on model performance, system health, and deployment status.

Experience:

• Proven experience as an MLOps Architect or similar role with a focus on AWS SageMaker.
• Extensive experience in deploying and managing machine learning models in a production environment.
• Strong understanding of cloud infrastructure, particularly AWS services (e.g., EC2, S3, Lambda, EMR, Eventbridge, CloudFormation).

Skills:

• Proficiency in Python and familiarity with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI, and Terraform)
• Strong knowledge of containerization technologies (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work independently and as part of a team.