AIML Compiler & Runtime Software Engineer

Sr Staff Engineer AI/ML Compiler & Runtime Software Engineer

AI SDK Team

Location: Pune / Bangalore India

Join the RISC-V Revolution!

About GlobalFoundries

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Introduction

We are seeking a highly skilled Sr Staff Engineer in AI/ML compiler and runtime software to join our Platform Software and AI SDK team. The team is building the foundational software stack to enable Physical AI workloads on next-generation RISC-V IP and SoC platforms.

This role sits at the intersection of AI compiler technology edge AI deployment runtime systems and hardware acceleration. You will work on IREE-based compiler and runtime flows LLVM/MLIR infrastructure custom MLIR dialects and passes code generation quantization and NPU acceleration to enable efficient execution of AI models on edge devices and silicon platforms.

This is a unique opportunity to contribute across the full silicon-to-software lifecycle combining compiler engineering AI runtime development and hardware-software co-design to deliver high-performance low-latency and power-efficient AI execution for real-time edge and Physical AI use cases.

What Youll Do

• Architect design and develop AI/ML compiler and runtime software for RISC-V based IP NPU and SoC platforms.

• Develop and enhance IREE-based compiler flows including MLIR lowering code generation runtime integration and deployment paths for edge AI workloads.
  Create and maintain custom MLIR dialects compiler passes lowering pipelines and transformation flows to map AI workloads efficiently to custom NPU and accelerator hardware.

• Work across AI framework import paths including PyTorch ONNX and TFLite and enable lowering through torch-mlir TOSA Linalg and related MLIR dialects.

• Optimize neural network workloads for edge deployment including operator fusion tiling memory planning quantization layout transformation and accelerator-aware scheduling.

• Enable efficient execution of AI models across CPU vector matrix and NPU acceleration paths balancing latency throughput memory footprint and power efficiency.

• Collaborate closely with architecture hardware firmware FPGA validation and product teams to bring up AI workloads on simulators FPGA platforms emulation environments and silicon.

• Analyze model performance identify compiler/runtime bottlenecks and drive optimizations across graph-level operator-level and kernel-level execution paths.

• Define software architecture and technical direction for AI SDK components including compiler pipelines runtime interfaces model deployment flows and accelerator integration.

• Build test infrastructure validation flows benchmark suites and CI pipelines for AI compiler/runtime correctness performance and regression tracking.

• Provide technical leadership to engineers working on AI compiler runtime model deployment and edge AI software development.

• Work with internal and customer-facing teams to support software enablement debugging performance tuning and deployment of AI workloads on target platforms.

Ideally youll have

• 3-12 years of hands-on software engineering experience with strong experience in compiler runtime embedded software or AI/ML systems.

• Strong hands-on experience with IREE LLVM and MLIR compiler infrastructure.
  Experience developing MLIR dialects compiler passes lowering pipelines pattern rewrites code generation flows or backend integration for custom hardware.

• Good understanding of IREE code generation flow dispatch formation executable generation HAL/runtime concepts and target-specific lowering.

• Strong exposure to AI compiler/runtime stacks used for edge AI or accelerator-backed inference.

• Experience with AI model formats and frameworks such as PyTorch ONNX TensorFlow Lite/TFLite and related conversion or import flows.

• Working knowledge of torch-mlir TOSA Linalg tensor dialects bufferization quantization dialects and MLIR-based model lowering concepts.

• Strong understanding of neural network execution and optimization including quantization operator fusion tensor layouts memory planning tiling vectorization and kernel selection.

• Experience enabling or optimizing workloads for AI accelerators NPUs DSPs vector processors matrix engines or custom SoC IP.

• Strong C/C programming skills with good Python scripting ability for compiler tooling testing automation and model workflow integration.

• Experience working in Linux development environments including cross-compilation debugging profiling build systems and runtime bring-up.
  Strong debugging and problem-solving skills across compiler IR generated code runtime behavior and hardware/software interaction.

• Ability to work with architecture and hardware teams to understand accelerator capabilities and translate them into compiler/runtime enablement.

• Proven ability to technically lead complex software modules mentor engineers and drive execution across cross-functional teams.

You might also have

• Experience working on RISC-V ARM x86 DSP GPU or custom accelerator software stacks.

• Familiarity with RISC-V Vector matrix acceleration concepts custom instructions or accelerator-specific code generation.

• Experience with edge AI deployment on real devices development boards FPGA platforms emulators simulators or early silicon.

• Familiarity with FPGA prototyping Linux bring-up board-level debugging or pre-silicon software validation.

• Exposure to LLM and edge inference stacks such as GGML/GGUF ONNX Runtime TensorFlow Lite TVM XNNPACK or similar frameworks with understanding of quantization memory footprint optimization kernel performance and deployment constraints on resource-limited devices.

• Experience with AI model benchmarking and optimization for vision audio transformers GenAI robotics automotive industrial or real-time embedded workloads.

• Understanding of hardware-software co-design memory hierarchy DMA scratchpad memory cache behavior and accelerator data movement.
  Experience with runtime systems kernel libraries microkernels custom dispatch flows or accelerator runtime APIs.

• Familiarity with CI/CD and agile tools such as Jenkins Git CMake Bazel Jira or similar engineering infrastructure.

• Experience working in customer-facing enablement silicon bring-up platform software or SDK delivery environments.

• Excellent communication and interpersonal skills with the ability to explain complex compiler and AI runtime topics clearly to software hardware and product stakeholders.

GlobalFoundries is an equal opportunity employer cultivating a diverse and inclusive workforce. We believe having a multicultural workplace enhances productivity efficiency and innovation whilst our employees feel truly respected valued and heard.

As an affirmative employer all qualified applicants are considered for employment regardless of age ethnicity marital status citizenship race religion political affiliation gender sexual orientation and medical and/or physical abilities.

All offers of employment with GlobalFoundries are conditioned upon the successful completion of background checks medical screenings as applicable and subject to the respective local laws and regulations.