Principal AI Compiler Engineer

www.enchargeai,com

AI Compiler Engineer-Staff/Principal

Locations: Bangalore (Hybrid) /Remote

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Responsibilities

• Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
• Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges.
• Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations.
• Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR).
• Implement parsing, semantic analysis, and IR generation for deep learning frameworks.
• Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers.
• Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).

• 10-20 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.

• Open-source contributions to AI software frameworks and libraries is a plus

• Demonstrated experience leading and mentoring engineering teams with successful project delivery

• skills

• MLIR

• Pytorch

• compilers

• "graph compilers"

• Torch-Fx

• "hardware Architecture"

• GPU

• TPU

• NPU

• "Neural networks"

• tensorflow

• AI

• ML

• DL

Contact:

Uday

Mulya Technologies

muday_bhaskar@yahoo.com

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