KERNEL ENGINEER

The role

You will write and optimize GPU kernels and supporting systems software for training and inference workloads. You will profile workloads, co-design kernels with research teams, and integrate optimizations into training and serving stacks.

What you will do

• Write and optimize GPU kernels for training and inference workloads
• Profile real workloads with hardware counters and translate findings into kernel-level optimizations
• Co-design kernels with research teams
• Integrate optimized kernels into training and serving stacks
• Benchmark and verify optimizations end-to-end
• Maintain kernel quality as hardware, frameworks, and workloads shift
• Spread kernel-level fluency across the team

Required qualifications

• 4+ years writing performant GPU kernels (CUDA, ROCm, Triton, or production-grade equivalent)
• Hardware-level fluency: memory hierarchy, occupancy, register pressure, tensor cores, warp scheduling
• Profiling fluency (Nsight, ncu, or comparable tools)
• Track record of shipping kernel-level optimizations that moved a measurable metric in a real system
• Strong systems expertise
• Comfortable reading framework-level Python and C++ around your kernels

Nice to have

• Open-source contributions to kernel libraries, compilers, or ML frameworks
• Experience with multiple accelerator architectures (different GPU families, TPUs, custom ASICs), preferably AMD GPUs
• Familiarity with collective communication primitives (NCCL or equivalent)
• Compiler or runtime background

About the company

makermaker.ai is a small, well-funded team building autonomous research agents for recursive self-improvement.