About the RoleWe 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 formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production.
- Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design.
- Improve AI-assisted optimization systems for specialized tasks through better datasets, evaluations, benchmarking, and research infrastructure.
- Partner across research and engineering teams to turn new ideas into practical systems spanning production needs and long-term infrastructure strategy.
You might thrive in this role if you have:- Strong systems or tooling engineering experience, with a background in low-level software, performance optimization, or infrastructure.
- Experience with developer tooling, debugging infrastructure, profiling, observability, or workflow design for technical users.
- Depth in kernel development, accelerator architecture, compiler systems, or related performance-critical domains.
- Familiarity with AI-assisted systems, agentic workflows, post-training, or reinforcement learning for engineering or research applications.
- Strong experimental judgment, comfort with ambiguity, and the ability to move fluidly between research exploration and production execution.
- Interest in compilers, DSLs, program synthesis, or AI for systems.
Preferred profileThe ideal candidate is a strong systems and tooling engineer with real depth in kernels and accelerators. They are comfortable working across software and hardware boundaries, can reason deeply about performance, abstractions, and system design, and have hands-on experience optimizing code for GPUs, high-performance CPUs, or custom accelerators. They view AI not as the end product, but as a force multiplier for engineering productivity and system optimization.
To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations.
