Member of Technical Staff, Kernel Engineering

The role

You will write kernels and low-level optimizations to make vLLM the fastest inference engine. You will work with hardware vendors to extract maximum performance from various accelerator types.

What you will do

• Write kernels and low-level optimizations
• Work with hardware vendors to ensure maximum performance from every generation of hardware

Required qualifications

• Bachelor's degree or equivalent experience in computer science, engineering, or similar
• Deep experience writing CUDA kernels or equivalent (CuTeDSL, Triton, TileLang)
• Strong understanding of GPU architecture: memory hierarchy, warp scheduling, tiling, tensor cores
• Proficiency in C++ and Python with demonstrated ability to write high-performance code
• Experience with profiling tools (Nsight, rocprof) and performance optimization methodologies
• Obsession with benchmarks and squeezing every percentage point of speedup

Nice to have

• Experience with ML-specific kernel optimization (FlashAttention, fused kernels)
• Knowledge of quantization techniques (INT8, FP8, mixed-precision)
• Familiarity with multiple accelerator platforms (NVIDIA, AMD, TPU, Intel)
• Experience with compiler technologies (LLVM, MLIR, XLA)
• Kernel-related contributions to vLLM or other inference engine projects
• Contributions to open-source GPU, ML systems, or compiler optimization projects
• Written deep technical blogs on GPU optimization

Benefits

• medical, dental, and vision coverage

Before you apply

• We sponsor visas on a case-by-case basis

About the company

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware.