Summary
✨ AI‑Generated
An AI DevOps engineering role focused on deploying and operating machine learning systems in production. You will manage cloud and on-premises infrastructure including GPU resources, build CI/CD pipelines, automate deployments with Python, and improve monitoring, reliability, and security.
Highlights
Hands-on role operating AI/ML systems in production, with exposure to GPU infrastructure, high-performance computing, cloud and on-premises environments, CI/CD, automation, monitoring, and security.
Description
Role: AI DevOps Engineer
Location: Plano, TX
Responsibilities:
AI/ML Deployment and Operations: Deploy, monitor, and maintain AI and ML models in production environments, ensuring performance and reliability Infrastructure ManagementProvision, configure, and maintain cloud and on-premises infrastructure, including GPU servers and high-performance computing resources CI/CD Pipeline DevelopmentBuild and manage continuous integration and continuous deployment pipelines for AI applications Automation and ScriptingAutomate repetitive tasks, infrastructure provisioning, and model deployment using scripting languages like Python CollaborationWork closely with cross-functional teams, including engineers, data scientists, and product managers, to design and implement AI solutions Monitoring and SecurityImplement monitoring, logging, and security best practices to ensure AI systems operate safely and efficiently Documentation and TrainingCreate technical documentation and provide training to end-users or team members on AI system usage and maintenance
Required Skills:
Proficiency in Python is essential; familiarity with other languages like Bash or Java is beneficial Cloud PlatformsExperience with cloud services such as AWS, Azure, or Google Cloud for AI deployment AI/ML KnowledgeUnderstanding of machine learning models, data pipelines, and AI frameworks (e.g., TensorFlow, PyTorch) is highly desirable DevOps ToolsExperience with CI/CD tools (Jenkins, GitLab CI), containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, Ansible) is important Problem-SolvingAbility to troubleshoot complex system issues and optimize AI workflows Communication: Strong collaboration and communication skills to work with technical and non-technical stakeholders
Regards,
Praveen Kumar R (Praveen)
Talent Acquisition Group – Strategic Recruitment Manager
praveen.r@themesoft.com| Themesoft Inc
