Software Engineer, GPU Kernels
Palo Alto, CA$200k - $420kPosted 1mo ago
About the role
GPU kernel engineer role focused on building and optimizing compute primitives for River AI's training and inference infrastructure, including attention, matrix multiplication, mixture-of-experts, and low-precision computation to accelerate large models.
Responsibilities
- Build fast GPU kernels for attention, matrix multiplication, expert routing, and related operations.
- Optimize memory access, tiling, and synchronization to make efficient use of GPU hardware.
- Develop FP8, FP4, and mixed-precision kernels while preserving numerical correctness.
- Accelerate fine-tuning and RL through optimized adapters, backward passes, and fused operations.
- Profile real workloads and integrate improvements into training and inference runtimes.
- Build reproducible benchmarks that verify correctness, gradients, and performance.
Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical experience.
- Experience optimizing GPU kernels with CUDA, Triton, CUTLASS, CuTe, or comparable tools.
- Strong understanding of GPU architecture, memory hierarchies, and parallel execution.
- Proficiency in C++ and Python.
- Strong foundations in linear algebra, floating-point arithmetic, and numerical computing.
- Strong debugging and profiling skills, with a collaborative approach to engineering.
Skills
Required:GPU kernel optimizationCUDA/Triton/CUTLASSC++PythonNumerical computingDebugging and profiling
Benefits
- Comprehensive health, dental, and vision insurance; unlimited PTO; relocation assistance as needed.
Last updated Sep 23, 2026. Interested? Apply on the company site.
About River AI
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