GPU Performance Engineer – Member of Technical Staff

About the role

We are seeking an experienced GPU Performance Engineer to design and implement improvements to our training infrastructure and to drive technical decisions that maximize the performance of large‑scale deep learning models. The role also covers post‑training processes such as reinforcement learning, fine‑tuning, and enhancing the efficiency of model serving.

Key responsibilities

• Design and implement enhancements to the training infrastructure for large deep‑learning models.
• Contribute to technical decisions that optimize GPU performance and model throughput.
• Develop and maintain post‑training pipelines, including reinforcement learning and fine‑tuning workflows.
• Improve the scalability and efficiency of model serving infrastructure.

Required profile

• Strong engineering background with fluency in Python and PyTorch (or similar frameworks).
• Proven experience building and training large deep‑learning models.
• Experience writing and debugging low‑level GPU code using CUDA and C++.
• Hands‑on experience scaling GPU jobs on large compute clusters (e.g., Slurm or Kubernetes).
• Ability to profile, identify bottlenecks, and apply performance‑tuning techniques to GPU‑accelerated workloads.

Required skills

• Python
• PyTorch
• CUDA
• C++
• GPU performance profiling
• Performance tuning
• Slurm
• Kubernetes

What we offer

• Five weeks of paid leave.
• Comprehensive healthcare benefits, including vision and dental coverage.
• Visa assistance for H‑1B and OPT transfers.