Nvidia Senior System Software Engineer - AI Performance Efficiency Tools 

United States, California 

64503711

What you’ll be doing:

• Build internal profiling and analysis tools for AI workloads at large scale

• Build debugging tools for common encountered problems like memory or networking

• Create benchmarking and simulation technologies for AI system or GPU cluster

• Partner with HW architects to propose new features or improve existing features with real world use cases

What we need to see:

• BS+ in Computer Science or related (or equivalent experience) and 5+ years of software development

• Strong software skills in design, coding (C++ and Python), analytical, and debugging

• Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference.

• Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking

• Experience with NVIDIA GPUs, CUDA Programming and NCCL

• Motivated self-starter with strong problem-solving skills and customer-facing communication skills

• Passion for continuous learning. Ability to work concurrently with multiple global groups

Ways to stand out from the crowd:

• Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms

• Solid experience in large AI job performance analysis for training/inference workload

• Knowledge of Linux device drivers and/or compiler implementation

• Knowledge of GPU and/or CPU architecture and general computer architecture principles