Software Development Engineer
Listed on Advanced Micro Devices (AMD)’s official careers site. Posted October 15, 2026. Check that it is still open and apply there.
Apply on Advanced Micro Devices (AMD)’s careers site →Job description
ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward.
Join us and, together, we’ll advance your career.
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 training and 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 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 C++ 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 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.
PREFERRED EXPERIENCE
Strong Programming Skills: Strong experience in C++ and/or Python, with demonstrated ability to debug, profile, and optimize performance-critical code.
SGLang and LLM Optimization
Solid 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
Strong experience running and scaling workloads on large-scale, heterogeneous clusters (CPU + GPU) using distributed training or inference strategies.
AI Framework Integration
Strong experience and contribution to or integrating optimizations into deep learning frameworks such as PyTorch or TensorFlow.
GPU Computing
Solid and strong knowledge of HIP, CUDA, 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, or a related field . #LI-SH1 Benefits offered are described: AMD benefits at a glance . AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.
We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.
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