AMD · 15 hours ago
Senior Software Development Engineer - SGLang
AMD is a company dedicated to building innovative products that enhance next-generation computing experiences. The role involves optimizing and developing deep learning frameworks for AMD GPUs, focusing on enhancing GPU kernel performance and collaborating with internal teams and open-source communities to drive contributions to AMD’s AI software ecosystem.
AI InfrastructureArtificial Intelligence (AI)Cloud ComputingComputerEmbedded SystemsGPUHardwareSemiconductor
Responsibilities
Optimize Deep Learning Frameworks: Enhance performance of frameworks like TensorFlow, PyTorch, and SGLang on AMD GPUs via upstream contributions in open-source repositories
Develop and Optimize Deep Learning Models: Profile and tune large-scale training and inference models for optimal performance on AMD hardware
GPU Kernel Development: Design, implement, and optimize high-performance GPU kernels using HIP, Triton, or other relevant tools for AI operator efficiency
Collaborate with GPU Library and Compiler Teams: Work closely with internal compiler and GPU math library teams to integrate and align kernel-level optimizations with full-stack performance goals
Contribute to SGLang Development: Support optimization, feature development, and scaling of the SGLang LLM framework across AMD GPU platforms
Distributed System Optimization: Tune and scale performance across both multi-GPU (scale-up) and multi-node (scale-out) environments, including inference parallelism and collective communication strategies
Graph Compiler Integration: Integrate and optimize runtime execution through graph compilers such as XLA, TorchDynamo, or custom pipelines
Open-Source Collaboration: Partner with external maintainers to understand framework needs, propose optimizations, and upstream contributions effectively
Apply Engineering Best Practices: Leverage modern software engineering practices in debugging, profiling, test-driven development, and CI integration
Qualification
Required
Strong technical and analytical expertise in C++ development within Linux environments
Ability to thrive in both collaborative team settings and independent work
Ability to define goals, manage development efforts, and deliver high-quality solutions
Strong problem-solving skills
Proactive approach
Keen understanding of software engineering best practices
Optimize Deep Learning Frameworks: Enhance performance of frameworks like TensorFlow, PyTorch, and SGLang on AMD GPUs via upstream contributions in open-source repositories
Develop and Optimize Deep Learning Models: Profile and tune large-scale training and inference models for optimal performance on AMD hardware
GPU Kernel Development: Design, implement, and optimize high-performance GPU kernels using HIP, Triton, or other relevant tools for AI operator efficiency
Collaborate with GPU Library and Compiler Teams: Work closely with internal compiler and GPU math library teams to integrate and align kernel-level optimizations with full-stack performance goals
Contribute to SGLang Development: Support optimization, feature development, and scaling of the SGLang LLM framework across AMD GPU platforms
Distributed System Optimization: Tune and scale performance across both multi-GPU (scale-up) and multi-node (scale-out) environments, including inference parallelism and collective communication strategies
Graph Compiler Integration: Integrate and optimize runtime execution through graph compilers such as XLA, TorchDynamo, or custom pipelines
Open-Source Collaboration: Partner with external maintainers to understand framework needs, propose optimizations, and upstream contributions effectively
Apply Engineering Best Practices: Leverage modern software engineering practices in debugging, profiling, test-driven development, and CI integration
Bachelor's and/or Master's Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
Preferred
Expert in C++ and/or Python, with demonstrated ability to debug, profile, and optimize performance-critical code
Solid hands-on experience with SGLang or similar LLM inference frameworks
Background in compiler design or familiarity with technologies like LLVM, MLIR, or ROCm
Expert experience running and scaling workloads on large-scale, heterogeneous clusters (CPU + GPU) using distributed training or inference strategies
Strong experience and contribution to or integrating optimizations into deep learning frameworks such as PyTorch or TensorFlow
Solid and strong knowledge of HIP, CUDA, or other GPU programming models; experience with GCN/CDNA architecture
Benefits
AMD benefits at a glance.
Company
AMD
Advanced Micro Devices is a semiconductor company that designs and develops graphics units, processors, and media solutions.
H1B Sponsorship
AMD has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
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Trends of Total Sponsorships
2025 (836)
2024 (770)
2023 (551)
2022 (739)
2021 (519)
2020 (547)
Funding
Current Stage
Public CompanyTotal Funding
unknownKey Investors
OpenAIDaniel Loeb
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