GPU Compute & MLIR Compiler Engineer (Bengaluru)

GPU Compute & MLIR Compiler Engineer (Bengaluru)

06 Aug
|
Recognized
|
Bengaluru

06 Aug

Recognized

Bengaluru

About the Company


We are hiring on behalf of our client, a global technology leader known for developing cutting -edge semiconductor, AI, graphics, and compute solutions powering next -generation mobile, automotive, IoT, and intelligent computing platforms. The company is at the forefront of AI acceleration, GPU architecture, and high -performance computing innovations.



Role Overview


We are seeking a GPU Compute & MLIR Compiler Engineer with strong expertise in GPU programming, MLIR compiler development, and AI workload optimization. The role involves designing and optimizing GPU compute kernels, developing MLIR -based compilation pipelines, and driving performance improvements for AI/ML applications across modern GPU architectures.



Key Responsibilities


- Develop and optimize GPU compute kernels for AI/ML workloads using OpenCL and Vulkan Compute.

- Design, build, and extend MLIR dialects and compiler infrastructure across multiple abstraction levels.

- Develop compiler passes including tiling, fusion, vectorization, bufferization, and lowering pipelines.

- Optimize AI model execution through compiler -level and runtime -level performance enhancements.

- Perform GPU profiling, bottleneck analysis, and performance tuning using hardware counters and profiling tools.

- Build and maintain GPU runtime components, including memory management, resource scheduling, and execution pipelines.





- Develop efficient code generation pipelines from MLIR to GPU backends.

- Collaborate with ML, runtime, framework, and hardware teams to optimize CV and LLM workloads.

- Develop high -performance compiler and runtime components using modern C/C++.


Required Skills


Compiler & MLIR

- Strong experience with MLIR framework.

- Hands -on experience creating custom dialects, compiler passes, and lowering pipelines.

- Knowledge of:

- TOSA, StableHLO, ONNX -MLIR

- Linalg, Tensor, Vector Dialects

- MemRef, SCF, GPU, LLVM Dialects

- Graph optimization and code generation techniques


GPU Programming

- Robust expertise in OpenCL kernel development and optimization.

- Experience with Vulkan Compute programming and runtime internals.

- Understanding of GPU architecture, memory hierarchy, parallel execution, and async compute.





- Experience profiling and optimizing GPU workloads.


Programming

- Strong proficiency in C/C++.

- Experience developing system -level software and performance -critical components.


AI/ML

- Good understanding of AI/ML fundamentals.

- Experience optimizing workloads related to:

- Computer Vision (CV)

- Large Language Models (LLMs)


Preferred Skills

- Experience with IREE, TVM, XLA, LLVM, or other MLIR -based deployment frameworks.

- Understanding of compiler/runtime architecture and hardware abstraction layers.

- Knowledge of quantization, mixed -precision inference, and model optimization.

- Exposure to multi -target compilation across CPU, GPU, and NPU.

- Familiarity with GPU profiling tools such as ARM Streamline, Intel VTune, Snapdragon Profiler, etc.

- Contributions to MLIR, LLVM, IREE, or related open -source projects.


Qualification

- Bachelor's/Master's/PhD in Computer Science, Electronics, Engineering, Information Systems, or related discipline.

- 4+ years of relevant experience in compiler development, GPU programming, AI acceleration, or systems engineering.




📌 GPU Compute & MLIR Compiler Engineer (Bengaluru)
🏢 Recognized
📍 Bengaluru

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