AI Software Engineer - Neuromorphic Computing

Job Details: Job Description: The Opportunity: For nearly a decade, Intel's Neuromorphic Computing Lab , together with a global ecosystem of 250 research groups, has explored architectures, algorithms, and software inspired by the brain's extraordinary efficiency, scalability, and adaptability. Our Loihi series of research chips pioneered event-driven, sparse, and massively parallel neuro-inspired processing, fueling over 100 peer-reviewed publications that validate the promise of this novel approach. Now, we're entering an exciting new chapter : transforming these breakthroughs into real-world products that will power the coming era of physical AI systems - beyond the reach of GPUs and mainstream AI accelerators. If you are passionate about pushing the boundaries of computing, from transistor-level innovation to software abstractions, join us. Help define the next wave of AI technology that harnesses the proven advantages of Intel's neuromorphic computing technology with the versatility demanded by modern AI workloads. Position Overview: In this role, you will drive the design, implementation, and optimisation of Intel's neuromorphic AI software stack, and collaborate with architects and cross-functional teams to deliver robust, efficient software solutions that enable developers and customers to build high-performance physical AI applications powered by Intel's neuromorphic technology. The Organisation: As part of Intel's CTO Office , you will join a vertically integrated incubation effort dedicated to bringing Intel's neuromorphic technology innovations to market. Our diverse team of engineers and researchers have pioneered sparse, event-based, neuromorphic architecture over multiple generations and is now focused on commercialising the technology in future Intel and partner products. Key Responsibilities: Design, implement, and test components of Intel's neuromorphic AI software stack, including model optimisation, compiler, and runtime modules. Collaborate with customers and partners to design optimised algorithms and applications. Partner with hardware architects to optimise HW/SW co-design for performance and scalability. Integrate neuromorphic software into leading robotics, IoT, and sensing frameworks to enable broad ecosystem adoption. Participate in code reviews, documentation, and continuous improvement of software processes. Assist in profiling and benchmarking software performance. Qualifications: Minimum Qualifications: MSc or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related field. 3 years of experience developing AI compiler, runtime, and profiling/debugging infrastructure in frameworks like Triton, MLIR, IREE, XLA, TVM, ONNX, or OpenVINO. 3 years of experience architecting and implementing production-grade software systems for maintainability, using standard engineering practices (profiling, benchmarking, correctness/performance regression testing, build/toolchain discipline, CI/CD). 5 years of experience with production software development in Python and C/C, including systems-level and performance-critical code. 3 years of experience with AI, deep learning, or optimization algorithms using frameworks such as PyTorch, JAX, or TensorFlow. Preferred Qualifications: Expertise in low-level systems and accelerator programming (CUDA, LLVM, OneAPI, OpenCL, SYCL) Familiarity with parallel computing paradigms and performance optimisation Experience with profiling and benchmarking algorithms and hardware architectures Knowledge of unconventional AI hardware accelerators and neuromorphic computing Background in robotics and robotic software frameworks (ROS2, Isaac, Holoscan) Experience defining software architecture roadmaps for emerging technologies Prior contributions to open-source projects Experience working in collaborative, cross-functional teams * Job posting details (such as work model, location or time type) are subject to change. Job ... (truncated, view full listing at source)