ML Compiler (Front-End) Engineer

Description

Summary: Seeking a Front-End Compiler Engineer to design, develop, and scale a Python-based compiler front-end for an AI/ML stack, focusing on model conversion pipelines and graph-level optimizations. Highlights: 1. Design and scale compiler front-end for AI/ML stack 2. Develop Python-based model conversion pipelines for popular ML frameworks 3. Implement graph-level optimizations and support modern deep learning **Type:** Contract (6\-9 months) **Location:** Remote \- Candidate must be based in and legally authorized to work in EU or US. **Role Overview:** We are seeking a **Front\-End Compiler Engineer** to design, develop, and scale the compiler front\-end for our AI/ML stack. This role focuses on building **Python\-based model conversion pipelines** that translate models from popular ML frameworks such as **ONNX, TensorFlow, and PyTorch** into our **internal Intermediate Representation (IR)**. The ideal candidate will work extensively on **graph\-level representations and optimizations**, support **modern deep learning architectures (including LLMs)**, and build **robust testing infrastructure** to ensure correctness, performance, and long\-term maintainability of the compiler front\-end. **Key Responsibilities:** * Design, develop, and maintain **Python\-based front\-end converter modules** to ingest models from **ONNX, TensorFlow, and PyTorch** into an internal IR. * Implement **graph construction, transformation, and IR lowering pipelines** as part of the compiler front\-end. * Analyze computation graphs and implement **graph\-level optimization passes**, such as operator fusion, simplification, and canonicalization. * Build and extend **pattern\-matching and graph\-rewriting frameworks** for scalable and maintainable optimizations. * Work on **model decomposition and conversion** of key building blocks used in **LLMs**, including attention mechanisms, MLPs, normalization layers, and embeddings. * Leverage and integrate tools from **ONNX Runtime** for model parsing, validation, and conversion workflows where applicable. * Develop and maintain **Python\-based testing infrastructure** for correctness validation, operator coverage, regression testing, and CI integration. * Debug and resolve issues across model ingestion, conversion, graph optimization, and IR generation stages. * Collaborate with backend compiler, runtime, and performance teams to ensure end\-to\-end model correctness and efficiency. **Required Skills \& Experience:** * **Strong Python programming skills (mandatory)** with an emphasis on clean, modular, maintainable, and well\-tested code. * Solid understanding of **compiler fundamentals**, including: \- Intermediate Representations (IRs) \- Graph\-based computation models \- Transformation and optimization passes * Hands\-on experience with **ML frameworks**, including **ONNX, TensorFlow, PyTorch**, and exposure to **Caffe**. * Practical experience in **graph parsing, transformation, and optimization** for ML models. * Familiarity with modern ML architectures, particularly **CNNs and Transformer\-based models**. * Experience building or contributing to **testing frameworks** for compilers, ML systems, or large Python codebases. * Strong debugging and problem\-solving skills across complex, multi\-stage pipelines. **Good to Have:** * Familiarity with **MLIR\-based front\-ends and dialects**, such as: **\- TOSA** **\- StableHLO** **\- Torch\-MLIR** * Exposure to AI compiler stacks, hardware backends, or accelerator targeting. * Experience working with large\-scale models or production ML inference/training pipelines. Job Type: Contract Contract length: 6\-9 months Application Question(s): * Are you legally authorized to work in EU or US? * Will you now or in the future require sponsorship for employment visa status to work in EU or US? Work Location: Remote