below marketmost similar roles pay hereabove market
This role pays more than
73%
of similar roles. Most pay
$170,712–$221,187
— the blue band above.
At the midpoint, this role pays about
$218k
versus about
$196k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
500 open roles
on FindRole.
Listed pay typically runs
$172,000–$258,000
across 500 roles with salary data.
JOB TITLE: Sr. Staff Distributed Systems Software Engineer, Collectives
As a Sr. Staff Distributed Systems Software Engineer, Collectives, you will join the Collectives and Network Performance team to optimize collective communication and networking software for AMD GPUs. You will design, implement, and optimize features in collective communication libraries across scale-up and scale-out networks to enhance training and inference performance on multi-GPU and multi-node systems. Your daily work involves profiling and tuning LLM, diffusion, multimodal, and generative AI workloads while developing benchmarking tools and infrastructure. You will utilize C++, Python, Linux, and libraries such as RCCL, NCCL, and MPI. You must possess deep knowledge of NIC, RDMA, and GPU hardware architectures. This role solves technical bottlenecks in distributed AI workloads by integrating optimizations into frameworks like PyTorch, JAX, vLLM, and SGLang.
Design, implement, and optimize collective communication features for scale-up and scale-out networks.
Profile and tune LLM, diffusion, and generative AI workloads on single-node and multi-node systems.
Drive assigned features from initial design and scoping through to delivery and performance validation.
Develop tools and infrastructure for benchmarking, performance estimation, and regression tracking.
Integrate code changes with internal GPU libraries and open-source maintainers to meet requirements.
Provide software performance data to inform the design of future networks and NICs.
Advise customers on load balancing, workload scheduling, and model sharding strategies.
Mentor junior engineers through code reviews and technical guidance.
What we're looking for
Experienced C++ developer with strong technical and analytical skills in Linux environments.
Solid knowledge of network, NIC, and GPU hardware architecture.
Hands-on experience profiling and optimizing distributed AI workloads.
Good understanding of modern training and inference optimization.
Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field (or a Bachelor’s degree with equivalent experience).
PhD is a plus (preferred).
Senior level of professional experience in technical software development, performance engineering, communication libraries, networking, or GPU/distributed systems (preferred).
Strong knowledge of collective communication libraries (e.g., RCCL, NCCL, MPI) and RDMA architectures (preferred).
CUDA
C++
Python
Deep Learning
Distributed Computing
PyTorch
JAX
TensorRT
vLLM
Triton
XLA
NCCL
MPI
UCX
Kernel Optimization
Model Optimization
FP8
INT8
Generative AI