Das ist der Job
You will directly influence the GPU efficiency, throughput, and scalability of mission‑critical AI systems.
Darum lohnt es sich
Location: Remote US
Start date: ASAP
Languages: English (required)
About the Role
Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital , founded by MIT CSAIL researchers.
We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale, high-throughput AI systems used by Fortune 500 customers.
This role is ideal for someone who deeply understands NVIDIA GPU architecture, memory hierarchy, warp-level execution, and profiling workflows not someone coming from generic hardware, FPGA, or non-NVIDIA compute backgrounds.
What Youll Do Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs , with a focus on maximizing occupancy, memory throughput, and warp efficiency. Profile GPU workloads using tools such as Nsight Compute, Nsight Systems, nvprof, and CUDA‑MEMCHECK .
Analyze and eliminate performance bottlenecks including warp divergence, uncoalesced memory access, register pressure, and PCIe transfer overhead . Improve GPU memory pipelines (global, shared, L2, texture memory) and ensure proper memory coalescing
