AI Kernel Engineer

Majestic Labs • Los Altos, CA

5d

About The Position

Design and implement high-performance compute kernels for AI primitives such as GEMM, attention, normalization, and convolution. Optimize throughput, latency, and memory hierarchy across heterogeneous compute units, including SIMD, matrix engines, and DMA. Collaborate with compiler and runtime teams to integrate kernels into Triton and PyTorch pipelines. Profile and tune kernels using tools such as Perfetto, VTune, Tracy, Nsight, or custom simulators. Prototype and evaluate precision formats, including FP16, BF16, FP8/e5m2, MXFP, and FP4. Contribute to micro-architecture feedback loops and help co-design ISA and memory features with the hardware team.

Majestic Labs is a fast-moving US-Israeli AI startup building custom AI servers for large-scale inference and training. The company describes its environment as collaborative and seeks curious, self-driven engineers who enjoy creative problem-solving and continuous learning. It is an equal opportunity employer committed to diversity of background and thought.

Requirements

• Degree at any level in Computer Science, Computer Engineering, or a related field from a recognized university.
• Strong background in parallel programming, such as CUDA, Triton, RISC-V Vector (RVV), POSIX Threads, or OpenMP.
• Deep understanding of memory layout, vectorization, thread/block scheduling, and cache behavior.
• Experience programming wide-SIMD vector units and matrix/systolic engines.
• Familiarity with the parallel-computing ecosystem and high-performance libraries and primitives, such as BLAS/BLIS, dense linear algebra, and parallel scan/reduce/sort.
• Skill in performance analysis and parallel debugging using tools such as GNU Debugger and Nsight.
• Hands-on experience profiling and optimizing compute or AI workloads, such as GEMM, softmax, or attention.
• Solid grasp of numerical stability, precision formats, and mixed-precision arithmetic.
• Proficiency in C++17 or higher, with strong knowledge of standard algorithms, data structures, and generic programming paradigms.
• Collaborative work style and ability to operate effectively in multicultural, cross-disciplinary environments.

Nice To Haves

• Experience optimizing irregular algorithms, such as graph computations or sparse numerical linear algebra, combining high-level data structure design with low-level SIMD and synchronization optimizations.
• Familiarity with LLVM/MLIR.
• RISC-V systems or bare-metal programming, including RISC-V vector and matrix extensions.

Responsibilities

• Design and implement high-performance compute kernels for AI primitives such as GEMM, attention, normalization, and convolution.
• Optimize throughput, latency, and memory hierarchy across heterogeneous compute units, including SIMD, matrix engines, and DMA.
• Collaborate with compiler and runtime teams to integrate kernels into Triton and PyTorch pipelines.
• Profile and tune kernels using tools such as Perfetto, VTune, Tracy, Nsight, or custom simulators.
• Prototype and evaluate precision formats, including FP16, BF16, FP8/e5m2, MXFP, and FP4.
• Contribute to micro-architecture feedback loops and help co-design ISA and memory features with the hardware team.

What This Job Offers

• Job Type: Full-time