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KLA AI Infrastructure Software Engineer 
United States, California, Milpitas 
376015701

Yesterday

Key Responsibilities:
  • Architect and implement robust software infrastructure to support AI/ML workloads across multiple frameworks and hardware platforms.
  • Design and optimize system-level components using C, C++, and Python, ensuring high performance, scalability, and maintainability.
  • Collaborate with multi-functional and cross-divisional teams to integrate AI frameworks (e.g., TensorFlow, PyTorch, JAX, ONNX) into a unified development environment.
  • Lead the development of build systems and toolchains using Makefiles, CMake, Clang, and GCC.
  • Stay ahead of modern software and AI trends, and guide the team in adopting standard processes and new technologies.
  • Provide technical leadership and mentorship to junior engineers and chip in to long-term architectural decisions.
Required Qualifications:
  • Education & Experience : Advanced degree in Computer Science, Electrical Engineering, or a related field, with a strong background in system-level software development.
  • Programming & Tools : Proficient in C, modern C++, Python, and experienced with Linux development environments. Familiar with build tools (Makefile, CMake), compilers (Clang, GCC), and container technologies (e.g., Kubernetes).
  • Technical Expertise: Deep understanding of software architecture, compiler toolchains, and runtime systems. Experience building infrastructure for AI/ML frameworks or high-performance computing environments.
  • Specialized Skills : Hands-on experience with CUDA, GPU programming, and familiarity with TensorFlow and deep learning model interoperability is a strong plus.
  • multi-functional Impact : Proven track record to develop scalable software infrastructure across multiple divisions or organizations.
  • AI & HPC Knowledge : Strong grasp of modern AI trends, including model optimization, distributed training, and inference acceleration.
  • Communication : Excellent written and verbal communication skills.
Preferred Qualifications
  • Experience working with AI accelerators or heterogeneous computing environments.
  • Contributions to open-source AI or systems software projects.
  • Strong collaboration skills, with the ability to influence and align partners across teams and geographies.

Minimum Qualifications

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