Member of Technical Staff - GPU Performance Engineer

At Liquid AI, we’re building novel model architectures that require GPU performance engineering beyond what standard frameworks can deliver.

You’ll design, implement, and optimize custom GPU kernels that make our models faster and more efficient across training, post-training, and inference. Working closely with researchers and engineers, you’ll identify performance bottlenecks, translate architectural innovations into efficient implementations, and deliver measurable improvements in production workloads.

This is a hands-on role for someone who enjoys understanding how GPUs actually execute code, from memory access patterns and warp scheduling to tensor core utilization. You’ll have the ownership to investigate complex performance problems, make informed engineering tradeoffs, and ship optimizations that directly impact how our models perform.

• Deliver measurable improvements in latency, throughput, or hardware efficiency for critical model workloads, validated through repeatable end-to-end benchmarks.