Principal AI Compiler Engineer

Principal AI Compiler Engineer (Staff/Principal)

About the Role:A pivotal opportunity at one of India's top emerging technology firms. This position offers hybrid work in Bangalore or remote flexibility.

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Key Responsibilities

• Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
• Collaborate closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, addressing specific hardware challenges.
• Execute performance optimizations for neural network models, including 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).

Experience: 10-20 years in compiler development with a strong focus on AI or ML graph compilers.

Tech Stack Proficiency:

• Ai graph compiler frameworks: MLIR, Torch-FX
• Hardware architectures (GPUs, TPUs, ASICs)
• Optimization techniques: fusion, quantization, tiling
• Familiarity with neural networks operators and code generation
• Deep understanding of intermediate representations, code parsing, semantic analysis
• Programming languages: C++, Python

Preferred: Open-source contributions to AI software frameworks; experience leading engineering teams.