Principal Compiler Engineer

The Heterogeneous Compiler Lab, led by esteemed technical experts with extensive industry and academic experience, publishes innovative research at leading conferences. Recognized as key contributors to the LLVM Compiler Infrastructure project, this lab excels in developing diversified IP compiler collaborations, focusing on AI, GPU, and CPU architectures. Our efforts include heterogeneous compilation technology and SW-HW co-design, optimizing for AI, graphics, games, and mobile applications while tackling technological challenges through open-source community.

• Design, develop, and test software to satisfy business requirements in a wide range of products.
• Analyze and optimize software system performance, and assist with software/hardware co-design.
• Liaise with internal and external stakeholders, determine project and feature requirements, and create development plans for software productization.
• Provide leadership in scrums, reviews, and project planning; engage in team building.
• Mentor junior developers through education sessions, code reviews, and career development.
• Research industry trends and paradigms, and propose new technical directions for the team.

• 8+ years of experience programming in large software projects with at least one of the following: C++, C, or Java.
• Satisfy at least two of the following:
  • Development or research experience in a production compiler (LLVM/Clang-based is an asset).
  • Development or research experience in a production language runtime (JVM-related is an asset), and/or design and implementation of a major programming language.
  • Development or research experience with deep learning frameworks and related ecosystem, such as Tensor Flow, Caffe2, MXNet, ONNX, TVM.
  • Development or research of GPU drivers, such as Vulkan, OpenGL, Direct
    
    X, or CUDA/OpenCL.
  • Development or research experience with hardware accelerators such as GPUs, NPUs, or FPGAs.
• Solid grasp of fundamental concepts related to system design, such as data structures, algorithms, and operating systems.
• In-depth understanding of computer processor architecture.
• Proficiency with software development tools and concepts such as source control, bug tracking, etc.
• Bachelor's, Master  degree or Ph.D (an asset). in Computer Science, Computer Engineering, or related field.
• The following items would be an asset:
  Deep understanding of IR and machine level compiler optimization techniques; experience in systems programming; proficiency in higher-level programming languages e.g. Go, Python; or an understanding of the implementation of higher-level programming languages.