AI Compiler Engineer

Responsibilities

• Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance and hardware utilization
• Work closely with ML researchers and hardware engineers to address hardware-specific challenges
• Perform performance optimizations such as layer fusion, operator fusion, and graph-level transformations
• Develop compiler optimizations and passes to convert high-level models from TensorFlow or PyTorch into intermediate representations
• Implement parsing, semantic analysis, and IR generation for deep learning frameworks
• Research and integrate advancements in compiler design and hardware acceleration
• Provide leadership, mentorship, and technical guidance to the engineering team

Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred)
• 3+ years in compiler development with a focus on AI or ML graph compilers
• Proficiency in AI graph compiler frameworks like MLIR or Torch-FX
• Solid background in hardware architectures such as GPUs, TPUs, or ASICs
• Knowledge of optimization techniques including fusion, quantization, and tiling
• Familiarity with neural network operators and code generation
• Strong understanding of intermediate representations, code parsing, and semantic analysis
• Proficiency in C++ or Python
• Experience leading and mentoring engineering teams

About the Company

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing, providing high-performance in-memory computing technology for power and energy-constrained applications.