AI Compiler Engineer-Engineer/Senior Engineer

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
- Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
- 2-4 years in compiler development, with a robust 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
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📌 AI Compiler Engineer (India)
🏢 Mulya Technologies
📍 India