GPU Kernel Optimization Specialist

2 days ago


Bengaluru, Karnataka, India beBeeAI Full time ₹ 1,04,000 - ₹ 1,30,878

Job Description:

We are seeking an experienced GPU kernel developer to join our team. As a key member of our core team, you will be responsible for developing high-performance kernels for state-of-the-art and upcoming GPU hardware.

Responsibilities:

  • Develop high-performance GPU kernels for key AI operators on AMD GPUs
  • Optimize GPU code using structured and disciplined methodology - profiling to identify gaps, roofline-analysis on hardware, identify key set of optimizations, establish uplift and line-of-sight, prototype and develop optimizations
  • Support mission-critical workloads in NLP/LLM, Recommendation, Vision and Audio
  • Collaborate and interact with system level performance architects, GPU hardware specialists, power/clock tuning teams, performance validation teams, and performance marketing teams to analyze and optimize training and inference for AI
  • Work with open-source framework maintainers to understand their requirements and have your code changes integrated upstream
  • Debug, maintain and optimize GPU kernels, understand and drive AI operator performance (GEMM, Attention, Distributed scale-up/out communication, etc.)
  • Apply your knowledge of software engineering best practices

Required Skills and Qualifications:

  • Experience in GPU computing (HIP, CUDA, OpenCL, Triton)
  • Knowledge and experience in optimizing GPU kernels
  • Expertise in using profiling, debugging tools
  • Core understanding of GPU hardware
  • Excellent C/C++/Python programming and software design skills, including debugging, performance analysis, and test design.

Preferred Experience:

  • Knowledge of GPU computing (HIP, CUDA, OpenCL, Triton)
  • Knowledge and experience in optimizing GPU kernels
  • Expertise in using profiling, debugging tools
  • Core understanding of GPU hardware
  • Excellent C/C++/Python programming and software design skills, including debugging, performance analysis, and test design.

Academic Credentials:

  • Masters or PhD or equivalent experience in Computer Science, Computer Engineering, or related field


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