GPU Performance Engineer

Job Summary

Experienced GPU Performance Engineers will find a full-time remote opportunity focused on designing and implementing enhancements to training infrastructure, optimizing model performance, and contributing to post-training processes such as reinforcement learning and fine-tuning.

Key responsibilities

• Design and implement improvements to training infrastructure for large-scale model training
• Analyze and optimize the performance of GPU-accelerated workloads, identifying bottlenecks and applying performance tuning techniques
• Contribute to post-training processes, including reinforcement learning and fine-tuning of models

Required qualifications

• Strong engineering skills with fluency in Python and experience with PyTorch or similar frameworks
• Proven experience in implementing and training large deep learning models
• Experience writing and debugging low-level GPU code (CUDA, C++)
• Familiarity with scaling GPU jobs using large-scale compute clusters (e.g., Slurm or Kubernetes)
• Demonstrated ability to analyze and optimize GPU-accelerated workloads