Founding Kernel Engineer, GPU Kernels

Touchdown Labs; EE. UU.; A distancia; USD 140.000 - 190.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Open-source contributions

Descripción de la vacante

Touchdown Labs is seeking a seasoned GPU kernel developer to design and qualify kernels for real-model workloads. You will work across framework dispatch, compilers, and device code, optimizing performance with reproducible measurements across accelerator architectures.

Responsibilities include identifying costly operators, implementing fused kernels, tracing through the stack, and building end-to-end performance evidence.

Formación

• Strong C++ and GPU programming fundamentals.
• Experience with CUDA, ROCm/HIP, Triton, or a comparable accelerator programming environment.
• Understanding of memory hierarchy, parallel decomposition, synchronization, precision, and numerical correctness.
• Ability to use profilers, disassemblers, and benchmarks to substantiate performance claims.
• Familiarity with framework dispatch and the compiler/runtime path around kernels.
• Ability to maintain architecture-specific guards, correctness coverage, and portable fallbacks.

Responsabilidades

• Find costly operators and execution gaps from representative workload traces.
• Implement, select, fuse, or generate kernels for relevant operations such as attention, matrix math, routing, normalization, and data movement.
• Trace framework operations through graph capture, compiler lowering, runtime dispatch, and device execution.
• Profile launch overhead, occupancy, instruction mix, memory traffic, synchronization, stalls, and numerical error.
• Compare vendor libraries, compiler paths, generated kernels, and custom implementations before taking on maintenance burden.
• Build correctness tests, benchmark harnesses, architecture guards, fallbacks, and end-to-end performance evidence.

Conocimientos

C++ & GPU

CUDA/ROCm/Triton

Memory hierarchy & parallelism

Profiling tools

Framework dispatch & compiler/runtime

Architecture guards & portable fall-b`

Descripción del empleo

Role overview

Develop and qualify GPU kernels that improve real model workloads while preserving numerical correctness. The work spans framework dispatch, compilers, device code, and profiling across accelerator architectures; optimization choices should be supported by reproducible measurements and an end-to-end workload benefit.

Responsibilities

• Find costly operators and execution gaps from representative workload traces.
• Implement, select, fuse, or generate kernels for relevant operations such as attention, matrix math, routing, normalization, and data movement.
• Trace framework operations through graph capture, compiler lowering, runtime dispatch, and device execution.
• Profile launch overhead, occupancy, instruction mix, memory traffic, synchronization, stalls, and numerical error.
• Compare vendor libraries, compiler paths, generated kernels, and custom implementations before taking on maintenance burden.
• Build correctness tests, benchmark harnesses, architecture guards, fallbacks, and end-to-end performance evidence.

Requirements

• Strong C++ and GPU programming fundamentals.
• Experience with CUDA, ROCm/HIP, Triton, or a comparable accelerator programming environment.
• Understanding of memory hierarchy, parallel decomposition, synchronization, precision, and numerical correctness.
• Ability to use profilers, disassemblers, and benchmarks to substantiate performance claims.
• Familiarity with framework dispatch and the compiler/runtime path around kernels.
• Ability to maintain architecture-specific guards, correctness coverage, and portable fallbacks.

Nice to have

Compiler IR or code generation; attention, GEMM, MoE, or communication kernels; collectives and multi-GPU execution; mixed-precision compute; or upstream open-source contributions.