✦ Luna Orbit — AI & Machine Learning

Opensource Al workload Software Engineer

at Advanced Micro Devices

📍 San Jose, California, United States Hybrid Posted March 27, 2026
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Position Details

Type Not Specified
Experience mid
Exp. Years Not specified
Education Bachelor's, Master's, or Ph.D. in Computer Engineering, Computer Science, Electrical Engineering, or related field
Category AI & Machine Learning

About this role

This role involves optimizing AI workloads on AMD GPUs at the kernel level, integrating open-source frameworks, and contributing to the future of AI computing infrastructure.

Key Responsibilities

  • Optimize GPU kernels
  • Integrate open-source frameworks
  • Contribute to AI infrastructure
  • Collaborate with hardware teams
  • Support community projects

Technical Overview

Focuses on GPU kernel optimization, open-source framework integration, and hardware-software co-design for AI workloads using HIP, CUDA, and related tools.

Ideal Candidate

The ideal candidate is a mid-level AI software engineer with expertise in GPU kernel optimization, open-source contributions, and experience with HIP, CUDA, and PyTorch frameworks. They demonstrate leadership and collaboration skills.

Must-Have Skills

Open-source contributionsGPU kernel optimizationHIPCUDAJAXPyTorch

Nice-to-Have Skills

XLATritonDeep AI infrastructure

Tools & Platforms

RoCmATenPyTorchJAXTritonHIPCUDAXLA

Required Skills

GPUKernel optimizationHIPCUDAXLAJAXPyTorchTritonOpen-source contributions

Hard Skills

Open-sourceAI workloadGPUKernel optimizationHIPCUDAXLAJAXPyTorchTriton

Soft Skills

Motivational leadershipInterpersonal skillsProblem-solvingCollaborationExploration

Industry & Role

Industry Semiconductor / Hardware
Job Function GPU kernel optimization and AI workload support for AMD hardware
Role Subtype AI Infrastructure Engineer
Tech Domains HIP, CUDA, XLA, JAX, PyTorch, Triton

Keywords for Your Resume

opensource ai workload software engineerGPUKernel optimizationHIPCUDAXLAJAXPyTorchTritonOpen-source contributionsAI workloadGPU performanceDeep AI infrastructureOpen-sourceMotivational leadership

Deal Breakers

Lack of GPU kernel optimization experience, No open-source contributions, No familiarity with HIP or CUDA

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