AI Infrastructure Engineer

Client of Eram Talent

Eram Talent is looking for a talented AI Infrastructure Engineer to join our innovative team.

Key Responsibilities:

• Design, implement, and manage high-performance computing environments tailored for AI and machine learning applications.
• Deploy and maintain GPU-accelerated clusters, cloud-based AI platforms, and parallel processing systems.
• Collaborate with data scientists and ML engineers to understand infrastructure requirements for various AI projects.
• Optimize resource allocation and scalability of AI infrastructure to support large datasets and complex models.
• Automate infrastructure provisioning and deployment using Infrastructure as Code (IaC) tools.
• Ensure security, compliance, and reliability of AI infrastructure.
• Monitor system performance and troubleshoot issues to minimize downtime and maximize productivity.
• Stay updated on emerging technologies and best practices in AI infrastructure and propose continuous improvements.

• Bachelor s or higher degree in Computer Science, Engineering, or related technical field.
• 3+ years of experience in infrastructure engineering, preferably with a focus on AI, machine learning, or high-performance computing environments.
• Cloud skills - GCP/OpenShift, Kubernetes (k8s), Docker containers/images
• AI skills Model training, testing/evaluation, deployment
• ML/LLMOPs
• LLMs and GenAI core skills how do LLMs work under the hood, inference mechanics of LLMs/GenAI
• Inference scaling, distributed computing, inference benchmarking, inference planning for meeting SLAs/SLOs
• GPUs and how to work with them, distributed workloads handling, autoscaling
• NVIDIA NIMs, Huggingface
• NVIDIA Superpods (HPC, slurm, k8s)
• Monitoring, dashboards for LLM/ML workloads and applications
• AI Application Architecture know-how, end to end flows
• DevOps (CI/CD, argoCD, git, Jenkins etc)
• Languages: Python, SQL