Software Engineer – GPU Kernel

5 months ago

Seoul, Korea, SouthMid Level

Responsibilities

Design, implement, and optimize high-performance GPU kernels for AI inference, including GEMM, attention, and routing.
Develop and maintain GPU code in CUDA and C++, including low-level assembly when needed.
Implement reduced-precision and quantized FP8 and FP4 kernels for low-latency and high-throughput inference.
Benchmark NVIDIA and AMD hardware and ensure cross-vendor performance parity.
Contribute to internal GPU libraries and tune performance-critical components.
Accelerate multimodal model pipelines.
Investigate and integrate next-generation GPU features.
Collaborate with the platform team to deploy optimized inference work into production.

3+ years of experience in GPU programming, HPC, or performance-critical systems.
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Strong proficiency in CUDA for NVIDIA GPUs or ROCm/HIP for AMD GPUs.
Deep understanding of GPU architecture, including warps, threads, memory hierarchy, synchronization, and latency-throughput trade-offs.
Proficiency in C++.
Experience with GPU profiling and performance tuning.
Strong numerical background, including precision trade-offs and quantization techniques.
Preferred experience optimizing transformer, multimodal, or Mixture-of-Experts architectures at the kernel level.
Familiarity with GPU libraries and frameworks such as CUTLASS and Triton.
Experience with inter-GPU communication programming.
Open-source contributions related to GPU performance or machine-learning acceleration.
Research or conference presentations on GPU optimization, HPC, or numerical computing.

Flexible working hours.
Daily lunch and dinner, plus unlimited snacks and beverages.
Supportive and highly collaborative work environment.
Health check-up support and top-tier equipment and hardware support.
Competitive compensation, startup equity, and health insurance.
The posting describes a small, fast-moving team working on generative AI infrastructure.

51-200 employees