Inferact is a startup founded by creators and core maintainers of vLLM, the most popular open-source LLM inference engine. Our mission is to grow vLLM as the world. Backed by Sequoia and Redpoint.
About the role
We're looking for a performance engineer to squeeze every FLOP out of modern accelerators. You'll write the kernels and low-level optimizations that make vLLM the fastest inference engine in the world. Your code will run on hundreds of accelerator types, from NVIDIA GPUs to emerging silicon. When hardware vendors develop new chips, they integrate with vLLM. You'll work directly with these teams to ensure we're extracting maximum performance from every generation of hardware.
What they're looking for
- Bachelor's degree or equivalent experience in computer science, engineering, or similar
- Deep experience writing CUDA kernels or equivalent (CuTeDSL, Triton, TileLang, Pallas)
- 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
More about this role
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—a position that took years to build.
We're looking for a performance engineer to squeeze every FLOP out of modern accelerators. You'll write the kernels and low-level optimizations that make vLLM the fastest inference engine in the world. Your code will run on hundreds of accelerator types, from NVIDIA GPUs to emerging silicon. When hardware vendors develop new chips, they integrate with vLLM. You'll work directly with these teams to ensure we're extracting maximum performance from every generation of hardware.
Bachelor's degree or equivalent experience in computer science, engineering, or similar.
Deep experience writing CUDA kernels or equivalent (CuTeDSL, Triton, TileLang, Pallas).
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...
Browse similar: AI jobs · AI startup jobs · Startup jobs · San Francisco Bay Area