Kernel Developer

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SeniorOn-site·GdańskFull-time·Umowa o pracę
#411206·Dodano dwa miesiące temu·12
Źródło: EER Poland
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Tech Stack / Keywords

C/C++AILinuxArchitectureCUDAOpenCL

Podsumowanie oferty

We are looking for a **C/**C++ engineer to design and optimize high-performance compute kernels for AI accelerators, focusing on user-space compute kernels for tensor operations used in deep learning workloads. The role involves working at the lowest level of AI performance engineering, where software meets specialized hardware. Responsibilities include designing, implementing, and optimizing compute kernels to improve latency, throughput, and efficiency on AI accelerators.

Wymagania

  • Strong proficiency in **C/**C++
  • Experience with performance-critical software development
  • Strong understanding of low-level optimization techniques
  • Understanding of CPU/GPU or accelerator architecture fundamentals
  • Ability to analyze and debug complex systems
  • Experience working with large, complex codebases
  • Strong communication and teamwork skills

Nice to have:

  • Experience with GPU kernel programming (CUDA / ROCm / OpenCL)
  • Experience with Triton or similar kernel programming frameworks
  • Knowledge of instruction set architectures (ISA)
  • Familiarity with compiler technologies (e.g., LLVM-based stacks)
  • Experience with distributed communication frameworks (NCCL, MPI, libfabric)
  • Understanding of deep learning models

Obowiązki

  • Design and implement high-performance compute (operator) kernels in **C/**C++
  • Develop core tensor operations
  • Optimize performance for AI accelerators, focusing on latency, throughput, and efficiency
  • Apply low-level optimization techniques
  • Profile, benchmark, and tune kernels to eliminate performance bottlenecks
  • Contribute to internal libraries and runtime systems for AI workloads

Benefity

  • Highly competitive salary with employment contract (Umowa o Pracę)
  • Comprehensive benefits package including Medicover healthcare coverage
  • Opportunity to work on performance-critical compute layer for next-generation AI accelerators
  • Direct impact on deep learning model efficiency and latency
  • Collaboration with experts in hardware, compilers, and systems
  • Challenging low-level performance engineering problems at the hardware–software boundary
Opieka zdrowotna
EER Poland

EER Poland

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