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Liquid AI Logo Liquid AI · IT - Software Development

Member of Technical Staff - GPU Performance Engineer

United States, San Francisco · Job Posted February 21, 2026
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Job Description

Our models and workflows require performance work that generic frameworks don’t solve. You’ll design and ship custom CUDA kernels, profile at the hardware level, and integrate research ideas into production code that delivers measurable speedups in real pipelines (training, post-training, and inference). Our team is small, fast-moving, and high-ownership. We're looking for someone who finds joy in memory hierarchies, tensor cores, and profiler output.

Job Responsibility

  • Write high-performance GPU kernels for our novel model architectures
  • Integrate kernels into PyTorch pipelines (custom ops, extensions, dispatch, benchmarking)
  • Profile and optimize training and inference workflows to eliminate bottlenecks
  • Build correctness tests and numerics checks
  • Build/maintain performance benchmarks and guardrails to prevent regressions
  • Collaborate closely with researchers to turn promising ideas into shipped speedups

Requirements

  • Authored custom CUDA kernels (not only calling cuDNN/cuBLAS)
  • Strong understanding of GPU architecture and performance: memory hierarchy, warps, shared memory/register pressure, bandwidth vs compute limits
  • Proficiency with low-level profiling (Nsight Systems/Compute) and performance methodology
  • Strong C/C++ skills

Nice to have

  • CUTLASS experience and tensor core utilization strategies
  • Triton kernel experience and/or PyTorch custom op integration
  • Experience building benchmark harnesses and perf regression tests

What we offer

  • Competitive base salary with equity in a unicorn-stage company
  • We pay 100% of medical, dental, and vision premiums for employees and dependents
  • 401(k) matching up to 4% of base pay
  • Unlimited PTO plus company-wide Refill Days throughout the year
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