Description Join our team as a DevOps Engineer specializing in Artificial Intelligence (AI) and Large Language Model (LLM) infrastructure. You will play a critical role in architecting, deploying, and optimizing scalable AI platforms using modern DevOps practices and state-of-the-art tools.
Key Responsibilities:- Build, automate, and manage CI/CD pipelines for deploying and maintaining AI/LLM workloads.
- Collaborate with AI engineers and data scientists to streamline model deployment, versioning, and monitoring.
- Design and maintain cloud infrastructure using Infrastructure as Code (IaC) platforms such as Terraform and Ansible.
- Orchestrate and manage containerized AI environments using Kubernetes.
- Implement robust monitoring and logging solutions utilizing Grafana and Prometheus.
- Optimize AI model inference and training workloads-especially for NVIDIA GPU-powered environments.
- Apply strict security and compliance standards for all infrastructure components.
- Diagnose and resolve production issues, continuously improving reliability and scalability of AI services.
Requirements Requirements:- Proven experience as a DevOps Engineer, preferably supporting AI or machine learning platforms.
- Hands-on expertise with Kubernetes (EKS, AKS, GKE, or on-prem), Docker, Terraform, and Ansible.
- Experience with monitoring/observability tools such as Grafana and Prometheus.
- Familiarity with NVIDIA GPU drivers, CUDA, and hardware provisioning for machine learning tasks.
- Proficiency in at least one scripting language (Python, Bash, etc.).
- Cloud platform experience (AWS, Google Cloud Platform, Azure); hybrid/on-premise a plus.
- Previous work with MLOps tools and data pipeline automation is highly desirable.
- Bachelor's degree in Computer Science or related field, or equivalent professional experience.
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