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Intel in Poland (Gdansk) is seeking a Compiler Engineer Intern to contribute to Intel's compiler software stack within a scoped project. You will work with experienced engineers on MLIR-based representations, DSLs, and optimization, while connecting capabilities to AI frameworks like PyTorch and inference engines.
You will investigate problems, implement and test solutions, and communicate results to the team.
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 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.
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 a scoped 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 involve connecting software 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 an undergraduate student who wants to build practical compiler-engineering experience and apply foundational computer science concepts to production software.
Bring your passion, curiosity, and your engineering drive to Intel, and help shape how the next generation of AI workloads runs on Intel hardware.
Job Type: Student / Intern Shift: Shift 1 (Poland) Primary Location: Poland, Gdansk Additional Locations:
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.
We offer a total compensation package that ranks among the best in the industry. The minimum Annual Salary for this job which could be performed in Poland is: 68 880,00 zł. The job posting reflects the minimum base compensation for this role. Our standard internship rates are aligned with the specific job role and degree level. As part of our total compensation approach, the final offer may also include additional pay components and benefits. Your recruiting team will provide the confirmed base salary along with any applicable total compensation elements upon employment offer delivery.
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site.
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