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Software Development

Distributed Systems Software Engineer, Collectives

  • $172k – $258k
  • |Remote ()
  • |Full Time
Posted: 2 weeks ago
Hires remotely in
Remote Work Policy

Remote only

Company Location
Visa Sponsorship

Not Available

RelocationAllowed
Skills
Python
C++
Software Development
Networking
Linux
Documentation
Debugging
Problem Solving
Profiling
MPI
Computer Architecture
RDMA
Written communication
testing
Gpu Architecture
Writing Tests
Verbal Communication
Networking concepts
eagerness to learn
Performance Engineering
Llm
Systems Software
PyTorch
Code Reviews
RecSys
Jax
Generative AI
vLLM
NCCL
Multimodal
Network Configurations
SGLang
AI Frameworks
Diffusion
NICs
Network Software
Interconnects
RCCL
Debugging Performance Issues
Performance Measurement Tools
Distributed Training Concepts
Collective Communication Libraries
AMD GPU Generations
Regression Tracking Tools
Collective Communication Concepts
Distributed Inference Concepts

About the job

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 RoleAs a member of the Collectives and Network Performance team, you will contribute to developing, testing and optimizing collective communication and networking software for AMD GPUs. You will help improve training and inference performance across multi-GPU and multi-node systems, working with senior engineers and with internal GPU library, runtime and ROCm teams, and learning how to integrate optimizations across AMD GPU generations and a range of AI models.The PersonSeeking a motivated C++ developer with a solid foundation in Linux environments, computer architecture and networking concepts. The ideal candidate completes well-defined tasks with guidance, learns quickly, and collaborates effectively within a high-performing team. You are comfortable profiling and debugging performance issues and are interested in how AI model architectures map onto software and hardware. Familiarity with GPU programming and distributed training or inference is a plus.Key ResponsibilitiesDevelop & Test Features: Implement, test and debug features in collective communication libraries and network software, under the guidance of senior engineers.Profile & Analyze Workloads: Profile LLM, diffusion, multimodal, RecSys and generative AI workloads on single-node and multi-node systems, and help identify performance bottlenecks.Run Benchmarks & Experiments: Run performance experiments across AMD GPU generations and network configurations, and summarize results for the team.Contribute to Tooling: Contribute to tools and infrastructure for performance measurement, regression tracking and reporting.Support Model & Framework Enablement: Support new model enablement and out-of-box performance efforts across AI frameworks, and work with internal teams and open-source communities to get changes reviewed and integrated.Software Engineering Best Practices: Follow sound engineering practices, including code reviews, testing and documentation, to deliver robust, maintainable code.Learn & Grow: Build expertise in collectives, networking and GPU performance through mentorship, code reviews, knowledge sharing and hands-on project work.Preferred ExperienceCollective Communication & Network Fundamentals: Understanding of collective communication concepts (e.g., all-reduce, all-to-all), and familiarity with libraries such as RCCL, NCCL or MPI and with networking fundamentals such as RDMA, NICs and interconnects.GPU Programming & Architecture: Foundational knowledge of GPU architecture; experience with HIP, CUDA or similar GPU programming is a plus.Deep Learning Frameworks: Familiarity with AI frameworks such as PyTorch, JAX, vLLM or SGLang and with distributed training or inference concepts.Software Engineering Fundamentals: Proficiency in C++ and Python, with experience in debugging, profiling and writing tests.Problem Solving & Communication: Strong problem-solving skills, eagerness to learn, and good written and verbal communication skills.Industry Experience: professional experience in software development, with exposure to performance engineering, systems software, networking, or GPU programming.Academic CredentialsBachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent LOCATION:San Jose, CA or Austin, TX - onsite.This role is not eligible for visa sponsorship.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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