AI Compiler Engineer

The role

You will architect, design, and implement optimizations for AI model execution on graph compilers. You will collaborate with hardware architects and AI researchers to enhance performance and enable efficient model deployment on EnCharge's Inference Accelerators.

What you will do

• Architect, design, and implement optimizations for AI model execution on graph compilers
• Work with ML researchers, hardware engineers, and software developers to design and deploy AI models
• Work on performance optimizations for neural network models like layer fusion, operator fusion, and graph-level transformations
• Develop compiler optimizations and passes that convert high-level AI models into intermediate representations
• Implement parsing, semantic analysis, and IR generation for deep learning frameworks
• Research and integrate advancements in compiler design, ML model optimizations, and hardware acceleration
• Provide leadership, mentorship, and technical guidance to a team of engineers

Required qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
• 3+ years in compiler development, with a strong focus on AI or ML graph compilers
• Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX)
• Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling
• Familiarity with neural networks operators and code generation
• Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design
• Proficiency in C++, Python, or other programming languages commonly used in compiler development
• Demonstrated experience leading and mentoring engineering teams with successful project delivery

Nice to have

• Ph.D.
• Open-source contributions to AI software frameworks and libraries

About the company

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. Launched in 2022, it is led by veteran technologists with backgrounds in semiconductor design and AI systems.