Advanced Micro Devices, Inc

Senior Software Development Engineer - SGLang and Inference Stack

Advanced Micro Devices, Inc • $130K — $180K *
Santa Clara, CA 95051In-Person
Information Technology
Less than 5 years of experience
Reposted Yesterday
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Job Overview by Ladders

Qualifications

  • 5-7 years of experience in GPGPU programming with C++ and have familiarity with Python.
  • Strong analytical skills and a problem-solving mindset for optimizing deep learning frameworks.
  • Experience with deep learning tools like TensorFlow, PyTorch, and SGLang.
  • Familiarity with compiler technologies such as LLVM, MLIR, or ROCm is beneficial.
  • Bachelor's or Master's Degree in Computer Science, Electrical Engineering, or related field.

Responsibilities

  • Enhance performance of deep learning frameworks on AMD GPUs.
  • Tune and optimize models for large-scale training and inference efficiency.
  • Design and implement high-performance GPU kernels for AI operations.
  • Collaborate with internal teams on optimizations and full-stack performance goals.
  • Support development and scaling of the SGLang framework on AMD GPUs.
  • Optimize performance across multi-GPU and multi-node environments.
  • Integrate and optimize runtimes with graph compilers and participate in open-source collaboration.

Benefits

  • Comprehensive healthcare and wellness programs for employees.
  • Flexible work hours and remote work opportunities.
  • Generous paid time off and vacation policies.
  • Commitment to diversity and inclusion in the workplace.
  • Access to professional development and training programs.
Full Job Description
THE ROLE:

As a core member of the team, you will play a pivotal role in optimizing and developing deep learning frameworks for AMD GPUs. Your work will be instrumental in enhancing GPU kernel performance, accelerating deep learning models, and enabling RL training and SOTA LLM and Multimodal inference at scale across multi-GPU and multi-node systems. You will collaborate across internal GPU software teams and engage with open-source communities to integrate and optimize cutting-edge compiler technologies and drive upstream contributions that benefit AMD's AI software ecosystem.

THE PERSON:

Skilled engineer with strong technical and analytical expertise in GPGPU C++, Triton, TileLang or DSL development within Linux environments. The ideal candidate will thrive in both collaborative team settings and independent work, with the ability to define goals, manage development efforts, and deliver high-quality solutions. Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices are essential.

KEY 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, analyze, code change and tune large-scale training and inference models for optimal performance on AMD hardware. Day-0 supports to many SOTA models, DeepSeek 3.2, Kimi K2.5, etc.
  • GPU Kernel Development: Design, implement, and optimize high-performance GPU kernels using HIP, Triton, TileLang or other DSLs for AI operator efficiency.
  • Collaborate with GPU Library and Compiler Teams: Work closely with internal compiler and GPU math library teams to integrate, optimize and align kernel-level optimizations with full-stack performance goals. Initiate and help with different level codegen optimizations.
  • Contribute to SGLang Development: Support optimization, feature development, and scaling of the SGLang framework across AMD GPU platforms for LLM, multimodal serving and RL-training.
  • Distributed System Optimization: Tune and scale performance across both multi-GPU (scale-up) and multi-node (scale-out) environments, including inference parallelism, prefill-decode disaggregation, Wide-EP 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/CD integration.


PREFERRED EXPERIENCE:
  • Strong Programming Skills: Proficient in C++ and/or Python (PyTorch, Triton, TileLang), with demonstrated ability to code, debug, profile, and optimize performance-critical code.
  • SGLang and LLM Optimization: Hands-on experience with SGLang or similar LLM inference frameworks is highly preferred.
  • Compiler and GPU Architecture Knowledge: Background in compiler design or familiarity with technologies like LLVM, MLIR, or ROCm is a plus.
  • Heterogeneous System Workloads: Experience running and scaling workloads on large-scale, heterogeneous clusters (CPU + GPU) using distributed training or inference strategies.
  • AI Framework Integration: Experience contributing to or integrating optimizations into deep learning frameworks such as PyTorch, SGLang, vLLM, Slime, VeRL
  • GPGPU Computing: Working knowledge of HIP, CUDA, Triton, TileLang or other GPU programming models; experience with GCN/CDNA architecture preferred.


ACADEMIC CREDENTIALS:
  • Bachelor's and/or Master's Degree in Computer Science, Computer Engineering, Electrical Engineering, Physics or a related field.


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About Advanced Micro Devices, Inc

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Manufacturing & Automotive
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ
AMD
* Ladders Estimates

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