Software Engineer, Kernel Programming Model
AI Summary
Design and implement the PyTorch-native kernel programming model, including the integration layer, runtime environments, and abstractions for tensor operations and virtual ISA, to enable efficient kernel execution as native extensions within PyTorch.
About this 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.
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Skills
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