Develop and optimize low-level kernels and runtime components for AI inference
Improve performance of inference engines GPU platforms
Profile and debug system-level and hardware-level performance issues
Integrate support for new hardware architectures (Hopper, Blackwell, Rubin)
Collaborate with ML and backend teams to optimize end-to-end execution
Strong proficiency in C++, OR expertise in GPU programming with a focus on low-level high-performance coding and memory management
Experience in GPU programming or systems-level software development, e.g. operating system internals, kernel modules, or device drivers
Hands-on experience with profiling and debugging tools to identify performance issues on both CPUs and GPUs, and the ability to optimize code based on those findings
Solid understanding of CPU/GPU architecture and memory hierarchy
Experience with GPU computing programming: CUDA, ROCm, CUTLASS, Cute, ThunderKittens, Triton, Pallas, Mosaic GPU
Familiarity with ML inference runtimes (e.g. TensorRT, TVM)
Knowledge of Linux internals, drivers, or compiler toolchains
Experience with tools like perf, VTune, Nsight, or ROCm profiler
Familiarity with popular inference engines (e.g. such as vLLM, sglang, TGI)
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams