AI Systems Software Engineer - Neuromorphic Computing
Intel
- Location
- US, Oregon, Hillsboro
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 1,112 approvals (FY2023)
- Posted
- Aug 18, 2026
Skills
About this role
Job Details
Job Description: About the Organization 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 has pioneered sparse, event-based neuromorphic architectures over multiple generations and is now focused on commercializing the technology in future Intel and partner products .
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 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.
Qualifications
The Minimum qualifications are required to be initially considered for this position. Minimum qualifications listed below would be obtained through a combination of industry relevant job experience, internship experience and / or schoolwork/classes/research. The preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Minimum Qualifications
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,