CUDA Engineer for AI Frameworks & GPU Performance

Best AI Tools Wiki; Santa Clara (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Stock grants in leading semiconductor

Employee stock purchase plan

On-site gym and cafeteria

Patent bonuses

Job summary

NVIDIA is seeking a CUDA Engineer to optimize deep learning frameworks for GPU acceleration, focusing on kernel optimization, memory management, and performance tuning for training and inference workloads on our latest GPU architectures in Santa Clara.

You will collaborate with a world-class team to push the limits of parallel computing, tailor software for high-throughput AI workloads, and contribute to scalable tooling across NVIDIA's AI portfolio.

Qualifications

• 5+ years of CUDA/C++ programming experience
• Deep understanding of GPU architecture and parallel computing
• Strong background in computer architecture
• BS/MS/PhD in Computer Science or Electrical Engineering

Responsibilities

• Optimize kernels for GPU acceleration
• Memory management improvements for high-throughput workloads
• Performance tuning for training and inference workloads

Skills

CUDA

C++

GPU Computing

Deep Learning

Performance Optimization

Python

Education

BS/MS/PhD in Computer Science or Electrical Engineering

Tools

TensorRT

Triton

PyTorch

TensorFlowGPU

Job description

NVIDIA is seeking a CUDA Engineer to optimize deep learning frameworks for GPU acceleration, focusing on kernel optimization, memory management, and performance tuning for training and inference workloads on our latest GPU architectures in Santa Clara.

You will collaborate with a world-class team to push the limits of parallel computing, tailor software for high-throughput AI workloads, and contribute to scalable tooling across NVIDIA's AI portfolio.