Software Engineer, Kernel Performance & AI Tooling
OpenAI - San Francisco, California, United States
Posted Apr 17, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
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- Mental health support
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Schedule
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- Weekend work
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Application
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About this role
Software Engineer, Kernel Performance & AI Tooling San Francisco, California, United States About the Team OpenAI's Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI's supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: - Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. - Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. - Optimize production kernels end to end by
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