About the role
Responsibilities
PyTorch-Native Kernel Programming Model: Design the integration layer and runtime environments that enable custom kernels to execute as native extensions within the PyTorch ecosystem.
Tensor-Level Kernel Language: Develop high-level abstractions and programming models to enable efficient model integration and expressive tensor operations.
Virtual ISA: Implement architectural abstractions that resolve performance bottlenecks through direct hardware control while maintaining high-level programmability.
Kernel Developer Ecosystem: Build core programming tools, technical specifications, and reference implementations to enable seamless kernel development and community contributions.
Minimum Qualifications
Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
Experience in systems programming such as Rust, C++, or Go with a deep understanding of computer architecture, including ISA, SIMD, and memory hierarchies.
Experience in designing and building clean, robust, and well-defined programming interfaces.
Preferred Qualifications
Master’s or PhD degree in Computer Science or a related technical field, or equivalent practical experience.
Experience in designing low-latency asynchronous execution models, kernel-level performance optimizations, or hardware-software co-design.
Experience in programming language theory and compiler infrastructure, including the design of domain-specific languages or intermediate representations using frameworks such as LLVM or MLIR.
Experience in engaging the developer community through open-source contributions, technical evangelism, or managing developer ecosystems.