Responsibilities

• Monitor and maintain AI systems for performance and reliability.
• Streamline data pipelines, model training, and deployment processes.
• Troubleshoot technical issues across software, hardware, and infrastructure.
• Collaborate with teams to deploy and integrate AI solutions seamlessly.
• Document processes, monitor system performance, and recommend improvements.
• Partner with data scientists, AI engineers, and IT teams to support the deployment and scalability of AI models. Facilitate seamless integration of AI solutions into business operations.
• Stay informed about emerging AI technologies and practices. Identify opportunities to incorporate new tools, frameworks, or techniques to enhance system capabilities.
• Implement security measures and ensure regulatory compliance.

Qualifications

• Degree in Computer Science, Engineering, or related field.
• Expert proficiency in Python, Java, or C++, with substantial experience in ML frameworks (e.g., TensorFlow, PyTorch).
• Expert-level familiarity with cloud platforms (AWS, Azure, GCP), containerization tools (Docker, Kubernetes), and CI/CD pipelines.
• Expertise in supporting and implementing bare metal Kubernetes environments.
• Extensive experience supporting diverse AI/ML models and using advanced MLOps tools (e.g., MLflow, Kubeflow).
• Hands-on expertise with big data tools and database management systems.
• Proven ability to troubleshoot and resolve complex technical issues effectively.
• Strong analytical, problem-solving, and organizational skills.
• Excellent communication and teamwork abilities, enabling effective collaboration across diverse teams.