Sr Staff AI/ML Compiler & Runtime Software Engineer

Job Title

Sr Staff AI/ML Compiler & Runtime Software Engineer

Role Summary

Senior software engineer on the Platform Software and AI SDK team responsible for compiler and runtime enablement for AI workloads on RISC-V IP, NPU, and SoC platforms. The role focuses on MLIR/LLVM-based compiler pipelines, IREE runtime integration, code generation, quantization, and hardware-aware optimizations for edge AI deployments.

Experience Level

Senior. Posting indicates 3–12 years of hands-on software engineering experience with compiler, runtime, embedded software, or AI/ML systems.

Responsibilities

Primary responsibilities include building compiler and runtime software to enable efficient AI model execution on edge and accelerator hardware.

• Architect, design, and implement AI/ML compiler and runtime components for RISC-V, NPU, and SoC platforms.
• Develop and extend IREE-based flows: MLIR lowering, code generation, runtime integration, and deployment paths for edge workloads.
• Create and maintain custom MLIR dialects, passes, lowering pipelines, and transformation flows for accelerator mapping.
• Support framework import paths (PyTorch, ONNX, TFLite) and enable lowering via torch-mlir, TOSA, Linalg, and related dialects.
• Optimize neural network workloads: operator fusion, tiling, memory planning, quantization, layout transforms, and accelerator-aware scheduling.
• Enable execution across CPU, vector/matrix units, and NPUs balancing latency, throughput, memory, and power.
• Collaborate with architecture, hardware, firmware, FPGA, validation, and product teams for bring-up on simulators, FPGAs, emulators, and silicon.
• Analyze performance, identify compiler/runtime bottlenecks, and implement graph-, operator-, and kernel-level optimizations.
• Define software architecture and technical direction for AI SDK components and deployment flows.
• Build test infrastructure, benchmarks, validation flows, and CI to ensure correctness and track regressions.
• Provide technical leadership, mentor engineers, and support customer enablement and debugging.

Requirements

Must-have skills and experience required to perform the role; followed by common nice-to-have items.

• 3–12 years of relevant software engineering experience in compilers, runtimes, embedded software, or AI/ML systems.
• Strong hands-on experience with IREE, LLVM, and MLIR: developing dialects, passes, lowering pipelines, pattern rewrites, code generation, or backend integration.
• Working knowledge of IREE code generation flow, dispatch formation, executable generation, and runtime/HAL concepts.
• Experience with AI model formats and frameworks: PyTorch, ONNX, TensorFlow Lite and related import/conversion flows.
• Solid understanding of neural network execution and optimization: quantization, fusion, layouts, memory planning, tiling, vectorization, and kernel selection.
• Experience enabling or optimizing workloads for NPUs, DSPs, vector/matrix engines, or custom accelerators.
• Strong C/C++ skills and Python for tooling, testing, and automation.
• Linux development experience including cross-compilation, debugging, profiling, build systems, and runtime bring-up.
• Proven ability to lead technical efforts, mentor engineers, and collaborate across cross-functional teams.
• Strong debugging and problem-solving skills across compiler IR, generated code, runtime behavior, and hardware/software interaction.
• Nice-to-have: experience with RISC-V/ARM/x86 accelerators, RISC-V Vector concepts, FPGA prototyping, LLM/edge inference stacks (llama.cpp, GGML, ONNX Runtime, TVM), and CI/CD tools (Jenkins, CMake, Bazel).

Education Requirements

Not specified.

About the Company

Company: GlobalFoundries

Headquarters: Saratoga Springs, New York, USA

GlobalFoundries is a leading contract manufacturer for the global semiconductor industry, with facilities in multiple countries, including the USA. The company develops a broad portfolio of semiconductor technologies and employs around 13,000 people worldwide. GlobalFoundries focuses on enhancing competitiveness in specialized application solutions and fostering innovation in mobile communications, consumer electronics, and automotive applications.