Description

You will manage GPU resource allocation, provisioning, and optimization across projects and departments.

This role is on-site.

Responsibilities

• Monitor GPU usage and performance metrics to identify bottlenecks and optimize resource utilization.
• Collaborate with IT and engineering teams to configure and maintain GPU infrastructure.
• Conduct performance analysis and tuning to improve rendering speeds, latency, and throughput.
• Work with software developers to resolve GPU-related performance issues.
• Maintain documentation for GPU configurations, software installations, and performance benchmarks.

Required Skills

• Strong understanding of GPU architecture and parallel computing principles.
• Proficiency in GPU programming languages such as CUDA or OpenCL.
• Experience using GPU profiling and performance analysis tools like NVIDIA Nsight or AMD Radeon Profiler.
• Familiarity with GPU-accelerated libraries and frameworks including cuDNN, TensorRT, OpenGL, or Vulkan.
• Analytical problem-solving skills with high attention to detail.
• Bachelor's degree or equivalent graduate level education.

Preferred Skills

• Knowledge of machine learning frameworks such as TensorFlow or PyTorch and deep learning concepts.
• Prior experience with GPU resource management or optimization.

Key Skills

Education

Any graduate