Lead Kernel EngineerArchitect

Were looking for a Lead Kernel Engineer/Architect to join our team in the Netherlands in a hybrid working mode.

Are you passionate about pushing advanced hardware accelerators to their limits Join us in shaping the future of AI performance and scalability.

As a Lead Kernel Engineer/Architect you will drive the optimization of critical machine learning operations for large-scale training and inference working with cutting-edge hardware like TPUs and GPUs advanced ML models and performance toolchains. Your work will enable faster AI research and production deployments on cloud platforms and within open-source ecosystems.

In this role you will collaborate with researchers compiler engineers and framework developers to deliver optimized high-performance solutions that set the standard for modern AI computation.

• Design and optimize high-performance kernels for TPU and GPU architectures using low-level programming frameworks such as Pallas Triton or Mosaic
• Build and maintain performance infrastructure including benchmarking suites autotuning systems regression testing frameworks and tooling
• Collaborate with ML framework developers (e.g. JAX PyTorch) and compiler teams (XLA/MLIR) to integrate custom kernels and reduce performance bottlenecks
• Track advancements in accelerator hardware compiler technology and AI model design to identify opportunities for kernel-level optimization
• Develop clear documentation APIs and supporting OSS components that improve developer usability and adoption
• Analyze and resolve complex performance issues impacting large-scale distributed training and inference systems

• Bachelors degree or equivalent practical experience
• 12 years of industry experience in software engineering or systems programming
• 5 years of experience in software development using C or Python
• 3 years of experience in testing maintaining or launching software products and at least 1 year in software design or architecture
• Hands-on experience in performance optimization at the kernel level for accelerators or high-performance systems

• Proficiency in low-level accelerator programming (CUDA Triton Pallas)
• Familiarity with ML frameworks such as JAX or PyTorch and optimization techniques for attention layers Mixture of Experts (MoE) and precision tuning
• Strong understanding of modern hardware accelerators including pipelining data movement and heterogeneous compute
• Knowledge of compiler principles and intermediate representations (e.g. MLIR OpenXLA)
• Experience building OSS developer infrastructure APIs and performance-critical libraries
• Excellent problem-solving skills and ability to collaborate in cross-functional engineering environments