퓨리오사AI Software Engineer, Compiler (Front-end)

한 줄 요약

퓨리오사AI Software Engineer, Compiler (Front-end) — 퓨리오사AI · Seoul, South Korea. 현재 상태: 진행·예정.

정보 갱신일 2026-10-21

조건·일정 확인

기관·대학

퓨리오사AI

지역·근무지

Seoul, South Korea

학력

학사 이상

담당 업무

• Faithful Ingestion: Translate models from external frameworks — with their evolving semantics, dynamic behaviors, and framework-specific constructs — into a precise internal representation that the rest of the compiler can reason about with confidence.
• Structural Optimization: Reshape programs at the graph level — through operator fusion, constant propagation, and shape resolution — so that downstream compilation stages receive the cleanest possible input.
• Tensor-Level Kernel Language Design: Design and evolve a programming language that enables users to directly author models optimized for FuriosaAI hardware. As the user-level interface to the compiler's internal IR and DSL, this language should maximize hardware performance while remaining intuitive for a broad range of users.
• Design and implement the front-end pipeline that transforms models from major deep learning frameworks such as PyTorch into the compiler's internal IR.
• Develop graph-level optimizations, including operator fusion, constant folding, shape inference, and layout transformations.
• Build extensible model ingestion structures that can accommodate new architectures such as LLM, VLA, and Multimodal models, and custom operators, while maintaining consistency and correctness.
• Design and evolve a tensor-level kernel language that exposes the capabilities of the internal IR and DSL through a consistent, well-abstracted user interface.
• Establish verification mechanisms to ensure correctness throughout the translation process.
• Collaborate with software teams and language users to maximize end-to-end compilation quality and refine the language design based on real-world usage patterns.

지원 자격

• Bachelor's degree in Computer Science, Mathematics, or a related field.
• Experience or familiarity with compilers, program transformation systems, or related infrastructure.
• Understanding of deep learning frameworks such as PyTorch, TensorFlow, and ONNX — and their model representations.
• Ability to abstract complex system constraints into consistent, user-friendly programming interfaces.
• Proficiency in Python and experience with at least one systems programming language such as Rust or C++.

우대 사항

• Master's or PhD in Programming Languages, Compilers, Program Analysis, or related fields.
• Experience designing and implementing domain-specific languages (DSLs) or user-facing programming models.
• Deep understanding of PyTorch compiler internals (TorchDynamo, FX Graph, torch.compile, torch.export) or kernel programming languages such as Triton.
• Research or industry experience with compiler frameworks such as LLVM, MLIR, or TVM.
• Understanding of AI accelerator architectures (NPU, GPU, TPU) and their implications for programming model design.
• Experience with graph-level compilation optimizations or contributions to open-source compiler and deep learning framework projects.
• talent@furiosa.ai

공식 출처와 다음 단계

원천 정보 갱신: 2026. 10. 21. PM 5:06

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