Description

You will lead research and optimization of GPU computing performance and AI infrastructure.

Responsibilities

• Design, implement, and fine-tune large-scale distributed systems for AI workloads.
• Conduct benchmarking and performance analysis for compute, storage, and networking components.
• Optimize servers, GPUs, networks, and databases for efficiency and scalability.
• Build, deploy, and manage containerized environments using Kubernetes, Rancher, and Kubeflow.
• Develop and maintain automation and debugging scripts, primarily in Python.

Required Skills

• 10+ years of experience with Kubernetes, containers, and distributed systems.
• 5–7 years in GPU computing performance and infrastructure research.
• Strong Python scripting skills.
• Deep knowledge of AI infrastructure optimization and debugging.
• Proficiency in benchmarking tools and performance tuning.
• Experience troubleshooting infrastructure issues across servers, GPUs, networks, and storage.

Key Skills

Education

Any Graduate