Experienced Software Engineer for Physical AI

About GF

GlobalFoundries (GF) is a leading manufacturer of essential semiconductors, enabling AI at scale from the cloud to the physical world. Through deep partnerships with customers, GF delivers differentiated, power-efficient and high-performance solutions for high-growth markets. With global manufacturing operations across the U.S., Europe and Asia, GF is a trusted and holistic technology partner for customers around the world. GF’s talented, global team remains focused every day on security, longevity and sustainability. For more information, visit www.gf.com.

Introduction

GlobalFoundries is seeking a Principal Member of Technical Staff (MTS) – Software Engineering with a strong AI compiler architecture focus to join the Physical AI SW Engineering team in Eindhoven, Netherlands. This senior, hands-on technical leadership role will define and evolve the architecture for production-ready AI toolchains targeting heterogeneous compute platforms, including neural processing units, vector accelerators, CPUs and related embedded systems. Working across globally distributed compiler, runtime, kernel, verification, infrastructure, hardware, product and customer-facing teams, you will translate product and customer requirements into scalable interfaces, technical direction and executable roadmaps.

Your Job

• Define and maintain the end-to-end architecture for AI compiler and toolchain capabilities across the Physical AI product portfolio.
• Translate product, model and customer use cases into compiler requirements, architecture specifications, interfaces, and prioritized technical roadmaps.
• Guide decisions across front-end model import, graph transformations, MLIR/LLVM-based intermediate representations, optimization, partitioning, scheduling, memory planning, code generation and deployment.
• Align compiler architecture with accelerator runtime, compute-kernel libraries, firmware, verification flows, and hardware architecture.
• Drive API and ABI consistency, portability and reuse across products while establishing clear extension points for product-specific capabilities.
• Lead architecture reviews, design reviews, technical risk assessments and proof-of-concept work for critical or novel features.
• Partner with engineering leads to decompose architectural direction into implementable epics, milestones and acceptance criteria.
• Analyze performance and quality gaps using representative AI workloads, then guide optimization across the full software and hardware stack.
• Collaborate with global teams, customers and ecosystem partners on integration, enablement, issue resolution and forward-looking requirements.
• Mentor compiler engineers and strengthen architecture practices, documentation quality and engineering standards across the organization.

Other Responsibilities

• Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.

Required Qualifications

• Bachelor’s, master’s or PhD in Computer Science, Electrical Engineering, Applied Mathematics or a related field, or equivalent practical experience.
• Extensive industry experience in compiler development, including senior technical ownership or architecture responsibility for complex software products.
• Strong knowledge of compiler design, intermediate representations, optimization, analysis, scheduling, memory management and code generation.
• Hands-on experience with LLVM and/or MLIR.
• Experience compiling for heterogeneous targets such as AI accelerators, NPUs, DSPs, GPUs, vector processors or embedded CPUs.
• Proficiency in modern C++ and Python, with the ability to prototype, review code and diagnose issues across system boundaries.
• Strong written and verbal communication skills and experience influencing decisions across distributed, cross-functional teams.

Preferred Qualifications

• Experience with AI compiler technologies such as IREE, XLA or TVM.
• Understanding of AI frameworks and interchange formats such as PyTorch, TensorFlow, TFLite and ONNX, including graph conversion and deployment flows.
• Experience with performance analysis, benchmarking and optimization of compute-intensive workloads.
• Working knowledge of low-precision inference, quantization, tensor layouts, operator fusion and hardware-aware optimization.
• Familiarity with agile development, CI/CD, automated testing, build systems and collaborative engineering tools.
• Project management skills, including the ability to innovate, execute solutions that matter and navigate ambiguity.
• Strong planning and organizational skills.

Expected Salary Range

The exact Salary will be determined based on qualifications, experience and location.