# Member of Technical Staff - GPU Performance Engineer at Liquid AI

- Company: Liquid AI
- What the company does: Liquid AI builds efficient Liquid Foundation Models (LFMs) for on-device, edge, and cloud AI with low latency, privacy, and hardware-aware deployment.
- Company website: https://www.liquid.ai
- Type: Startups (AI role)
- Level: Senior
- Location: San Francisco
- Work setup: Remote
- Posted: 2025-07-29
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/liquid-ai/dfc3bae5-003f-4438-b51a-4cdfdb4199ba
- Page: https://www.1752.vc/careers/jobs/liquid-ai-member-of-technical-staff-gpu-performance-engineer/

## About the role

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.

## What they're looking for

- 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

Tags: Research & Engineering