Compiler Engineer - Triton and DSLs

About This Role

• Join Us in Shaping the Future The world is transforming, and so is Intel.
• Intel is a company of bold and curious inventors and problem solvers who create some of the most astounding technology advancements and experiences in the world.
• With a legacy of relentless innovation and a commitment to bringing smart, connected devices to every person on Earth, our diverse and brilliant teams are continually searching for tomorrow's technology and embracing the challenge of changing the world for the better.
• Role Overview Join our compiler team and contribute to the design, development, and optimization of AI compiler technologies for Triton, Domain Specific Languages (DSLs) and emerging AI programming models.
• Our team develops software that enables high-performance execution of AI, enabling developers to write highly efficient GPU kernels that power modern machine learning frameworks.
• You will work on modern compiler infrastructures including LLVM and MLIR, helping deliver technologies that improve performance, scalability, programmability, and portability across diverse hardware architectures.
• This role offers opportunities to contribute to open-source ecosystems while solving challenging problems in code generation, compiler optimization, runtime integration, and developer productivity.
• By joining us, you'll help build the software foundations that enable developers and researchers to unlock the full potential of Intel's AI and accelerator platforms.
• Key Responsibilities: • Design, implement, test, and debug compiler features for DSLs, Triton, and related programming models. • Develop compiler optimizations, analyses, and transformations that improve application performance and scalability. • Contribute to compiler front-end, middle-end, or code-generation technologies. • Collaborate with hardware architects, compiler engineers and AI framework developers to enable new platform capabilities. • Contribute to open-source compiler projects and communities where appropriate. • Continuously learn and apply emerging technologies in compilers, AI software, and heterogeneous computing.