Software AI Compiler Engineer

We seek an innovative and highly skilled Software AI Compiler Engineer to join our team. The ideal candidate will have extensive experience in compiler development, with specific expertise in MLIR and LLVM frameworks. This role involves designing and implementing advanced compiler optimizations for AI and machine learning workloads, enabling high performance and efficiency. 

Responsibilities: 

• Design, develop, and maintain compiler components using MLIR and LLVM. 
• Implement advanced optimizations to improve the performance and efficiency of AI and machine learning models. 
• Collaborate with AI researchers and software engineers to define compiler requirements and specifications. 
• Optimize code generation for various hardware targets, including CPUs, GPUs, and specialized AI accelerators. 
• Debug and resolve compiler-related issues, ensuring robustness and reliability. 
• Stay updated with the latest advancements in compiler technology, AI, and machine learning. 
• Contribute to open-source compiler projects and collaborate with the wider compiler development community. 
• Document design decisions, implementation details, and usage instructions for compiler components. 
  
  

• Bachelor’s or master’s degree in computer science, Engineering, or a related field. 
• 3 years of experience in compiler development with a strong understanding of MLIR and LLVM. 
• 5 years of experience in C++ and familiarity with other programming languages such as Python. 
• Strong understanding of AI and machine learning principles and frameworks. 
• Experience with performance profiling and optimization techniques. 
• Excellent problem-solving skills and attention to detail. 
• Ability to work both independently and as part of a team. 
• Strong communication skills to effectively collaborate with other team members and stakeholders. 
  
  

• Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, or ONNX. 
• Familiarity with heterogeneous computing environments and hardware accelerators. 
• Knowledge of software development methodologies, including Agile and Scrum. 
• Experience contributing to open-source projects. 
• Understanding of parallel computing and multi-threading.