AI/ML Compiler & Runtime Software Engineer
GlobalFoundries (company site, opens in a new tab)3–12 yrsPuneOn-siteDirect career pageEst. 35–55 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Architect and develop AI/ML compiler and runtime software for RISC-V based IP, NPU, and SoC platforms focusing on IREE and MLIR infrastructure.
- Optimize neural network workloads for edge deployment including quantization, operator fusion, memory planning, and accelerator-aware scheduling for efficient AI model execution.
- Lead technical direction, build test infrastructure, and collaborate with cross-functional teams to enable and deploy AI workloads on simulators, FPGA, emulation, and silicon platforms.
Minimum Requirements
- 3-12 years of hands-on software engineering experience in compiler, runtime, embedded software, or AI/ML systems.
- Strong experience with IREE, LLVM, MLIR compiler infrastructure including dialect development, passes, code generation, and backend integration for custom hardware.
- Proficient in AI model frameworks and formats such as PyTorch, ONNX, TFLite and relevant compiler import/lowering paths.
- Strong C/C++ programming skills with Python scripting ability; experience in Linux development environment including cross-compilation, debugging, and profiling.
Ideal Candidate Profile
- Experience in AI compiler/runtime stacks targeting edge AI or accelerator-backed inference with knowledge of MLIR-based model lowering and code generation.
- Ability to technically lead complex software modules, mentor engineers, and work closely with architecture/hardware teams translating accelerator capabilities into compiler/runtime features.
- Familiarity with RISC-V or other accelerator architectures, edge AI deployment on real hardware platforms (FPGA, emulators, silicon), and hardware-software co-design concepts.