AI Frameworks Engineer

Location: Gdansk, Poland. Hybrid work model with time split between the assigned Intel site and off-site work.

Annual salary: 215,740–388,330 PLN.

Company

Develops data-center technologies and open software infrastructure for high-performance artificial intelligence workloads.

What you will do

• Design, develop, and optimize AI framework software for LLM inference on Intel GPUs.
• Contribute upstream to open-source frameworks including vLLM and PyTorch.
• Develop and tune compute kernels for attention, mixture-of-experts, quantization, normalization, and other transformer operations using technologies such as Triton and SYCL.
• Implement distributed execution paths covering tensor, pipeline, and data parallelism, collective communication, and asynchronous data movement.
• Profile workloads, identify hardware-level performance bottlenecks, and optimize implementations for different memory hierarchies, instruction sets, and execution models.
• Build unit tests, correctness checks, and performance regression coverage while collaborating with framework, compiler, machine learning, and open-source communities.

Requirements

• Bachelor's degree in AI, Computer Science, Computer Engineering, Mathematics, Physics, or a related field.
• At least 2–3 years of relevant experience with a bachelor's degree or 1+ year with a master's degree.
• Advanced Python programming skills and demonstrated proficiency with PyTorch internals or extension mechanisms.
• Hands-on experience with AI inference and large language models, plus a solid foundation in AI frameworks, machine learning algorithms, and software engineering.
• Strong debugging, problem-solving, and optimized software or algorithm design skills, with proficiency in Linux environments.
• Ability to work in the hybrid Poland-based setup.

Nice to have

• Experience writing or optimizing GPU kernels with Triton, CUDA, SYCL, OpenCL, or similar technologies.
• Experience profiling and optimizing AI workloads using hardware-level performance data.
• Knowledge of parallel and distributed computing, collective communication libraries, vLLM, or other LLM inference serving frameworks.
• Accepted contributions to major open-source AI projects.
• Understanding of numerical precision and FP8, INT8, and INT4 quantization formats.

Culture & Benefits

• Flexible working hours and a safe work environment at home or on company premises.
• Technical and soft-skills training, innovation projects, and rotational programs.
• Stock program, annual and quarterly bonuses, and an employee pension plan.
• Medical and life insurance, restaurant and multisport cards, employee discounts, recognition programs, and community events.