AI Compiler Engineer

Job Title

AI Compiler Engineer

Role Summary

Develop and optimize graph compilers and compiler passes to enable efficient execution of AI/ML models on EnCharge AI inference accelerators. Work closely with hardware architects, ML researchers, and software engineers to translate high-level models into optimized intermediate representations and backend code.

Focus on performance, latency reduction, and maximizing hardware utilization for edge-to-cloud deployments.

Experience Level

Mid-level — typically requires 3+ years of experience in compiler development, with emphasis on AI/ML graph compilers.

Responsibilities

Core responsibilities include designing, implementing, and integrating compiler optimizations for AI models.

• Architect, design, and implement optimizations for AI model execution on graph compilers to improve throughput and reduce latency.
• Implement compiler passes and transformations such as layer/operator fusion and graph-level optimizations.
• Convert high-level models (TensorFlow, PyTorch) into intermediate representations and generate backend code.
• Implement parsing, semantic analysis, and IR generation for deep learning frameworks.
• Collaborate with ML researchers and hardware engineers to address hardware-specific constraints and map operators efficiently to accelerators.
• Research and integrate advances in compiler design, model optimizations, and hardware acceleration.
• Provide technical leadership and mentorship to engineers working on graph compiler optimizations.

Requirements

Must-have skills and experience.

• 3+ years in compiler development focused on AI/ML graph compilers.
• Proficiency with graph compiler frameworks (e.g., MLIR, Torch-FX).
• Practical experience implementing compiler passes, operator fusion, and graph transformations.
• Strong background in hardware architectures (GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling.
• Familiarity with neural network operators, code generation, and backend mappings.
• Solid understanding of intermediate representations, parsing, and semantic analysis in compiler design.
• Proficiency in C++ and Python.
• Demonstrated experience leading and mentoring engineering teams and delivering projects.
• Nice-to-have: open-source contributions to AI frameworks and experience with quantized inference backends.

Education Requirements

Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or a related field; Ph.D. preferred. Equivalent practical experience will be considered.

About the Company

Company: EnCharge AI

EnCharge AI develops advanced AI hardware and software systems for edge-to-cloud computing, focusing on in-memory computing technology to deliver high compute efficiency and density with low power consumption. Founded in 2022, the company targets power-, energy-, and space-constrained applications with integrated hardware architectures and software stacks for scalable, reliable AI deployment.