AI Kernel Engineer

We’re a fast-moving, US-Israeli AI startup building next-generation infrastructure for the world’s most demanding AI workloads. Our mission is to accelerate the future of intelligence and make it ubiquitously accessible by delivering full stack custom AI servers optimized for large-scale inference and training.

Backed by top-tier investors and led by industry veterans, we’re scaling rapidly. We seek forward-thinking engineers and operators who thrive in a collaborative environment and excel at solving complex challenges from first principles. If you want to build infrastructure that fundamentally changes what the world can accomplish with AI, come join us!

About The Position

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

• Degree at any level in Computer Science, Computer Engineering, or a related field from a recognized university.
• Strong background in parallel programming (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 its high-performance libraries and
• primitives, such as BLAS/BLIS, dense linear algebra, and parallel scan/reduce/sort.
• Skilled in performance analysis and parallel debugging using tools such as GNU Debugger and Nsight.
• Hands-on experience profiling and optimizing compute or AI workloads (e.g., GEMM, softmax, 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 with the ability to operate effectively in multicultural, cross-disciplinary environments.
  
  

• Experience with optimization of 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.