Remote GPU Performance Engineer: Scale Training & Inference

Reka

United States

Remote

USD 120,000 - 150,000

Full time

14 days+

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Benefits offered by this job

Five weeks of paid leave
Comprehensive healthcare benefits
Visa support for H1B and OPT transfers

Job summary

A global AI foundation model startup is seeking an experienced GPU Performance Engineer to enhance training infrastructure and optimize model performance. The ideal candidate will have strong skills in Python and experience with large-scale model training, including GPU code optimization. This role offers a collaborative environment featuring top-tier talent and generous benefits, including extensive paid leave and visa support. Join a team committed to AI innovation and excellence.

Qualifications

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

Responsibilities

  • Design and implement improvements to training infrastructure.
  • Contribute to technical decisions optimizing model performance.
  • Work on post-training processes including reinforcement learning and fine-tuning.
  • Improve efficiency and scalability of model serving infrastructure.

Skills

Fluent in Python
Proficient in PyTorch
Experience with CUDA
Large scale model training
Performance optimization

Job description

A global AI foundation model startup is seeking an experienced GPU Performance Engineer to enhance training infrastructure and optimize model performance. The ideal candidate will have strong skills in Python and experience with large-scale model training, including GPU code optimization. This role offers a collaborative environment featuring top-tier talent and generous benefits, including extensive paid leave and visa support. Join a team committed to AI innovation and excellence.
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