About the Job

The compiler is central to FuriosaAI's mission to build high-performance, energy-efficient AI systems. The front end is where the compiler meets the outside world. Its mission spans three areas:

• 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.

We are looking for someone who thinks in systems, designs for extensibility, and brings rigor and clarity across the stack — from model ingestion to user-facing language design.

Responsibilities

• 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.

Minimum Qualifications

• 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++.

Preferred Qualifications

• 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.

Contact

• recruit@furiosa.ai