AI Systems Software Engineer - Neuromorphic Computing

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 low-level hardware enablement to software abstractions and applications, join us. Help define the next wave of AI technology that combines the proven advantages of Intel's neuromorphic computing technology with the versatility demanded by modern AI workloads.

Position Overview

Join the team defining and implementing Intel's product-grade neuromorphic AI software stack. In this role, you will develop and validate systems software that enables Intel neuromorphic accelerators, spanning device interfaces, operating system integration, runtime APIs, simulation environments, and integration with higher-level AI and application frameworks. You will collaborate with hardware, software, and solution architects to deliver robust, efficient, and scalable software that enables customers to build high-performance physical AI applications powered by Intel's neuromorphic technology.

Responsibilities

• Design, develop, and validate system-level software for future neuromorphic accelerator platforms, including device-driver interfaces, operating system integration, runtime APIs, and simulation environments.
• Analyze functional and performance issues across software drivers, runtimes, and applications; implement improvements and develop supporting profiling, debugging, benchmarking, and validation tools.
• Collaborate with hardware, architecture, operating-system, and application teams to enable upcoming platform features, recommend hardware and software improvements, and ensure expected functionality and performance on next-generation systems.

• BS in Computer Science, Computer Engineering, Electrical Engineering, or a closely related engineering discipline.
• 5+ years of industry experience developing and validating production software for GPUs, AI accelerators, embedded devices, or other hardware platforms, including work across device drivers, runtime systems, APIs, simulation environments, or application frameworks.
• 5+ years of production software development experience in C or C++ and Python, including systems-level or performance-critical software.
• Experience designing, debugging, integrating, and validating software across hardware, operating system, driver, runtime, and application boundaries.
• Experience applying standard software engineering practices, including design and code reviews, profiling, benchmarking, correctness and performance regression testing, build and toolchain discipline, and CI/CD.

• Post graduate degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related engineering discipline
• Experience developing Linux device drivers, hardware abstraction layers, low-level runtime libraries, or platform services for GPUs or other accelerators.
• Experience with low-level systems and accelerator programming technologies such as LLVM, oneAPI, OpenCL, SYCL, or CUDA.
• Experience developing tools for hardware and software validation, profiling, debugging, tracing, or performance analysis.
• Experience with hardware and software co-design, hardware simulator development, or performance modeling.
• Experience with robotics, edge AI, or real-time systems, including frameworks such as ROS 2.
• Experience with AI, deep learning, or optimization workloads and frameworks such as PyTorch, JAX, TensorFlow, ONNX, OpenVINO, or IREE.

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. Job posting details (such as work model, location or time type) are subject to change.

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.