performance engineer
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Role details
Tech stack
Job description
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.
Requirements
- 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.
Preferred qualifications:
- 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).
Benefits & conditions
- Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.
- Visa sponsorship: We sponsor visas on a case-by-case basis.
- Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.
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-a position that took years to build.
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