Sr. Staff Distributed Systems Software Engineer, Collectives
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Before you apply
LocationUS,TX,Austin, United States
Typefull-time
SeniorityLead
DepartmentEngineering
Company size10,000+ people
First seenOct 30, 2026 · 6d ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or Bachelor's degree with equivalent experience)
Strong knowledge of collective communication libraries (e.g., RCCL, NCCL, MPI) and understanding of NIC, RDMA and network architectures
Strong experience in profiling, performance analysis and bottleneck identification for distributed AI workloads
Hands-on experience integrating optimized compute or communication into ML frameworks (PyTorch, JAX, vLLM, SGLang)
Strong proficiency in C++ and Python with solid experience in performance tuning, debugging and test design
Experience with large-scale, multi-node compute environments and optimizing AI workloads across clusters
Ability to work effectively with cross-functional teams, mentor less experienced engineers, and communicate results clearly
Senior level of professional experience in technical software development, with focus on performance engineering, communication libraries, networking, or GPU/distributed systems
PhD is a plus
Not eligible for visa sponsorship
Skills
C++
Python
Linux
RCCL
NCCL
MPI
PyTorch
JAX
vLLM
SGLang
RDMA
NIC
GPU
Benefits
Health insurance
401(k)
Remote stipend
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 an experienced member of the Collectives and Network Performance team, you will play an important role in optimizing collective communication and networking software for AMD GPUs. You will enhance communication libraries and training/inference performance across multi-GPU and multi-node systems, working with internal GPU library, runtime and ROCm teams and with open-source maintainers to integrate optimizations across multiple generations of AMD GPUs and a range of state-of-the-art AI models.
THE PERSON:
Seeking an experienced C++ developer with strong technical and analytical skills in Linux environments. The ideal candidate can take ownership of features and projects with limited guidance, contribute to defining scope and technical approach, and collaborate effectively within a high-performing team. You have solid knowledge of network, NIC and GPU hardware architecture, hands-on experience profiling and optimizing distributed AI workloads, and a good understanding of modern training and inference optimization. You also support the growth of less experienced engineers.
KEY RESPONSIBILITIES:
•
Develop Collective Communication Features: Design, implement and optimize features in collective communication libraries across scale-up and scale-out networks.
•
Optimize Distributed Training & Inference: Profile, tune and analyze LLM, diffusion, multimodal, RecSys and generative AI workloads on single-node and multi-node systems, and recommend design tradeoffs.
•
Own Features End to End: Drive assigned features and projects from design through delivery with limited guidance, including scoping, implementation, testing and performance validation.
•
Performance Modeling & Tooling: Develop and improve tools and infrastructure for benchmarking, performance estimation, regression tracking and reporting.
•
Collaborate with Framework & Library Teams: Work with internal GPU library, runtime and ROCm teams, and with open-source maintainers, to ensure code changes meet requirements and are integrated upstream.
•
Hardware-Software Co-Design Input: Contribute software performance data and analysis to discussions on future scale-up networks, NICs and scale-out networks.
•
Customer & Stakeholder Support: Help customers and internal teams apply effective load balancing, workload scheduling and model sharding strategies, and present results and recommendations.
•
Software Engineering Best Practices: Apply sound engineering principles to deliver robust, maintainable solutions.
•
Guide & Mentor: Mentor junior engineers through code reviews, knowledge sharing and technical guidance.
PREFERRED EXPERIENCE:
•
Collective Communication & Network Knowledge: Strong knowledge of collective communication libraries (e.g., RCCL, NCCL, MPI) and a good understanding of NIC, RDMA and scale-up and scale-out network architectures.
•
Performance Analysis: Strong experience in profiling, performance analysis and bottleneck identification for distributed AI workloads.
•
Deep Learning Integration: Hands-on experience integrating optimized compute or communication into ML frameworks such as PyTorch, JAX, vLLM or SGLang, with a focus on throughput and scalability.
•
Software Engineering Excellence: Strong proficiency in C++ and Python with solid experience in performance tuning, debugging and test design.
•
High-Performance Computing: Experience with large-scale, multi-node compute environments and optimizing AI workloads across clusters.
•
Collaboration & Communication: Ability to work effectively with cross-functional teams, mentor less experienced engineers, and communicate results clearly.
•
Industry Experience: senior level of professional experience in technical software development, with a focus on performance engineering, communication libraries, networking, or GPU/distributed systems.
ACADEMIC CREDENTIALS:
•
Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field (or a Bachelor’s degree with equivalent experience). A PhD is a plus.
LOCATION:
Austin, Texas or San Jose, California.
This role is not eligible for visa sponsorship.
Benefits
Benefits offered are described: AMD benefits at a glance.
Legal
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.
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.
THE ROLE:
As an experienced member of the Collectives and Network Performance team, you will play an important role in optimizing collective communication and networking software for AMD GPUs. You will enhance communication libraries and training/inference performance across multi-GPU and multi-node systems, working with internal GPU library, runtime and ROCm teams and with open-source maintainers to integrate optimizations across multiple generations of AMD GPUs and a range of state-of-the-art AI models.
THE PERSON:
Seeking an experienced C++ developer with strong technical and analytical skills in Linux environments. The ideal candidate can take ownership of features and projects with limited guidance, contribute to defining scope and technical approach, and collaborate effectively within a high-performing team. You have solid knowledge of network, NIC and GPU hardware architecture, hands-on experience profiling and optimizing distributed AI workloads, and a good understanding of modern training and inference optimization. You also support the growth of less experienced engineers.
KEY RESPONSIBILITIES:
•
Develop Collective Communication Features: Design, implement and optimize features in collective communication libraries across scale-up and scale-out networks.
•
Optimize Distributed Training & Inference: Profile, tune and analyze LLM, diffusion, multimodal, RecSys and generative AI workloads on single-node and multi-node systems, and recommend design tradeoffs.
•
Own Features End to End: Drive assigned features and projects from design through delivery with limited guidance, including scoping, implementation, testing and performance validation.
•
Performance Modeling & Tooling: Develop and improve tools and infrastructure for benchmarking, performance estimation, regression tracking and reporting.
•
Collaborate with Framework & Library Teams: Work with internal GPU library, runtime and ROCm teams, and with open-source maintainers, to ensure code changes meet requirements and are integrated upstream.
•
Hardware-Software Co-Design Input: Contribute software performance data and analysis to discussions on future scale-up networks, NICs and scale-out networks.
•
Customer & Stakeholder Support: Help customers and internal teams apply effective load balancing, workload scheduling and model sharding strategies, and present results and recommendations.
•
Software Engineering Best Practices: Apply sound engineering principles to deliver robust, maintainable solutions.
•
Guide & Mentor: Mentor junior engineers through code reviews, knowledge sharing and technical guidance.
PREFERRED EXPERIENCE:
•
Collective Communication & Network Knowledge: Strong knowledge of collective communication libraries (e.g., RCCL, NCCL, MPI) and a good understanding of NIC, RDMA and scale-up and scale-out network architectures.
•
Performance Analysis: Strong experience in profiling, performance analysis and bottleneck identification for distributed AI workloads.
•
Deep Learning Integration: Hands-on experience integrating optimized compute or communication into ML frameworks such as PyTorch, JAX, vLLM or SGLang, with a focus on throughput and scalability.
•
Software Engineering Excellence: Strong proficiency in C++ and Python with solid experience in performance tuning, debugging and test design.
•
High-Performance Computing: Experience with large-scale, multi-node compute environments and optimizing AI workloads across clusters.
•
Collaboration & Communication: Ability to work effectively with cross-functional teams, mentor less experienced engineers, and communicate results clearly.
•
Industry Experience: senior level of professional experience in technical software development, with a focus on performance engineering, communication libraries, networking, or GPU/distributed systems.
ACADEMIC CREDENTIALS:
•
Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field (or a Bachelor’s degree with equivalent experience). A PhD is a plus.
LOCATION:
Austin, Texas or San Jose, California.
This role is not eligible for visa sponsorship.
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