AI Software Development Engineer - Neuromorphic Computing at 100 Intel Corporation

Compensation · Listed in posting

$170,500 – $240,710/yr

Setup: Hybrid
Location: Santa Clara, California
Type: Full-time
Level: senior
Posted: Oct 2, 2026

Description

Intel is hiring an AI Software Engineer in Neuromorphic Computing to develop high-performance kernels, programming abstractions, performance models, and optimized AI applications for sparse, event-driven, massively parallel neuromorphic hardware. The role spans kernel implementation, workload optimization, hardware-software co-design, simulation and emulation validation, benchmarking, and collaboration with hardware, compiler, runtime, and application teams. It is based in Santa Clara, California, with a hybrid work model, and offers an annual salary range of $170,500 to $240,710 USD.

Required Skills

Python
C/C++
CUDA
SYCL
PyTorch
JAX
TensorFlow
Kernel fusion
Quantization
Performance modeling

Additional Information

Minimum Education: PhD with no prior professional experience, or a master's degree with 2+ years of relevant experience, or a bachelor's degree with 4+ years of relevant experience in a technical field.
Required Previous Experiences: 4+ years developing, debugging, and delivering maintainable Python and C/C++ software, including performance-critical or systems-level code.
2+ years implementing and optimizing numerical, machine-learning, or high-performance computing kernels using parallel programming and an accelerator or domain-specific language.
2+ years developing, training, or evaluating AI algorithms and machine-learning models using PyTorch, JAX, or TensorFlow.
2+ years establishing numerical correctness and measuring performance using reference implementations, automated testing, benchmarking, profiling, or performance-regression infrastructure.
Preferred Qualifications: Experience developing or optimizing convolutional-network, transformer, generative-AI, or edge-AI workloads.
Experience with compiler technologies or domain-specific language development.
Experience with hardware performance modeling, architecture simulators, PPA analysis, or hardware-software co-design.
Advanced experience with kernel fusion, tiling, vectorization, quantization, sparsity, layout optimization, or double buffering.
Experience developing software for spatial, dataflow, neuromorphic, or other emerging AI accelerator architectures.
Experience contributing to collaborative or open-source software projects.