As an AI Software Engineer in Neuromorphic Computing at Intel, you will play a crucial role in transforming neuromorphic hardware capabilities into high-performance AI software. You will work closely with hardware architects and AI researchers to develop specialized kernels and optimize operations for various AI workloads. This position offers the opportunity to influence design decisions and contribute to the commercialization of innovative neuromorphic technology. Your expertise will help shape the future of AI systems that operate under tight latency and power constraints.

• A PhD with no prior professional experience, a master's degree with 2+ years of relevant experience, or a bachelor's degree with 4+ years of relevant experience in Computer Science, Electrical Engineering, Computer Engineering, Applied Mathematics, Physics, or a related technical field.
• 4+ years of experience developing, debugging, and delivering maintainable software in Python and either C or C++.
• 2+ years of experience implementing and optimizing numerical, machine-learning, or high-performance computing kernels using parallel programming and either an accelerator programming model, such as CUDA, SYCL, or OpenCL.
• 2+ years of experience developing, training, or evaluating AI algorithms and machine-learning models using a framework such as PyTorch, JAX, or TensorFlow.
• 2+ years of experience establishing numerical correctness and measuring performance using reference implementations, automated testing, benchmarking, profiling, or performance-regression infrastructure.

• Design and implement specialized AI kernels for neuromorphic hardware using custom DSLs and accelerator programming models such as CUDA and SYCL.
• Develop and optimize operations for convolutional networks, transformers, and generative AI workloads by applying techniques such as tiling, fusion, vectorization, parallelization, layout transformation, buffering, sparsity, and quantization.
• Develop performance methodologies and improve kernel behavior in areas such as compute utilization, latency, throughput, memory bandwidth, data movement, synchronization, and scaling.
• Build reference models, numerical validation tools, benchmarks, and analytical or simulation-based performance, power, and area models that guide hardware-software co-design.
• Collaborate with hardware, compiler, runtime, and application engineers to deliver maintainable code, tests, documentation, benchmarks, and performance-regression infrastructure.

• Intel offers a comprehensive benefits package including competitive pay, stock programs, healthcare coverage, retirement plans, paid time off, parental leave, and programs supporting employee wellbeing and professional development.