Compiler Engineering Graduate Intern

Location: Canada, Toronto

Job Details

Job Description

Join Us in Shaping the Future

At Intel, we are building the next generation of software technologies that unlock the potential of heterogeneous computing. Our compiler technologies help developers harness CPUs, GPUs, and accelerators through high-performance, portable software. As an intern, you will contribute to an open ecosystem that advances performance, scalability, reliability, and developer productivity for AI, HPC, and other demanding workloads, while supporting Intel's commitment to contributing to and collaborating with open-source communities.

The Team

The Intel Compiler Engineering Team develops LLVM-based C, C++, SYCL, Triton, MLIR, Domain Specific Languages (DSLs), and Fortran compiler technologies for Intel processor platforms, including CPUs and GPUs. The team works across the compiler stack and in close collaboration with hardware architecture teams, covering language front ends, intermediate representations, optimization, code generation, debug information, runtimes, offload support, quality, and developer tooling. This work connects Intel hardware and compiler capabilities with AI frameworks and software ecosystems such as PyTorch, inference engines, and machine-learning models. You will collaborate with experienced engineers and contribute to open-source communities while learning how production compilers are designed, tested, optimized, and delivered.

Position Overview

We are hiring a Compiler Engineer Intern to contribute to Intel's compiler software stack. You will work with experienced compiler and hardware architecture engineers on an engineering or research project that may involve compiler features, MLIR-based intermediate representations, Triton or other Domain Specific Languages (DSLs), optimization, code generation, runtime or offload support, debug information, testing infrastructure, performance analysis, or developer tools. Projects may connect hardware capabilities to AI frameworks such as PyTorch, inference engines such as vLLM and SGLang, and machine-learning model ecosystems such as DeepSeek, Hugging Face, and Qimi. You will investigate technical problems, implement and test solutions, analyze results, and communicate findings to the team. This opportunity is designed for a graduate student who can apply deeper technical expertise to an ambiguous engineering or research problem, evaluate alternatives, and deliver a well-supported solution or prototype.

Responsibilities

• Contribute to the design, implementation, testing, or analysis of compiler and runtime technologies.
• Develop and debug software in C or C++ within a large, collaborative codebase.
• Create or improve tests, reproduce defects, analyze failures, and help deliver reliable solutions.
• Evaluate functional correctness, compile-time behavior, runtime performance, or code quality, as applicable to the project.
• Participate in code reviews, technical discussions, and project planning with mentors and team members.
• Document designs, experiments, results, and lessons learned, and present project outcomes to the team.
• Contribute to open-source projects when aligned with the assigned work.

Success in This Role

• Curiosity and willingness to learn unfamiliar technologies.
• Strong analytical, problem-solving, and debugging skills.
• Clear written and verbal communication.
• Ability to work independently on scoped tasks while seeking guidance when needed.
• Collaborative mindset and commitment to high-quality engineering.

Qualifications

Minimum Qualifications

• Currently pursuing a Master's or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline.
• Graduate-level coursework, research, or project experience in compilers, programming languages, computer architecture, parallel computing, systems software, or a closely related area.
• Experience programming in C or C++ and working with complex software systems.
• Experience designing experiments, analyzing technical results, and communicating conclusions.

Preferred Qualifications

• Familiarity with LLVM, MLIR, Clang, Flang, SYCL/DPC++, Triton, OpenMP, CUDA, or another compiler or parallel-programming ecosystem.
• Hands-on experience with LLVM or related compiler infrastructure, including front-end development, intermediate representations, optimization passes, code generation, runtimes, or debug information.
• Research or development experience involving CPU/GPU architectures, heterogeneous computing, AI/ML compilation, HPC, parallel programming, or performance optimization.
• Experience with AI frameworks such as PyTorch, inference engines such as vLLM and SGLang, and machine-learning models such as DeepSeek, Hugging Face, and Kimi.
• Tile-base programming model knowledge
• GPU Compute kernel writing experience
• Experience contributing to open-source software or working in a large collaborative codebase.
• Publications, technical reports, patents, open-source contributions, or other evidence of advanced technical work.

Job Type:Student / Intern

Shift:Shift 1 (Canada)

Primary Location: Canada, Toronto

Additional Locations

Posting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/A

Annual Salary Range for jobs which could be performed in Canada

Salary range dependent on a number of factors including location and experience.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their