AI Networking Systems Software Engineer

Advanced Micro Devices, Inc•Santa Clara, CA

6d•Onsite

About The Position

AMD is looking for a AI Networking Systems Software Engineer who is passionate about improving the performance, reliability, and scalability of key applications, benchmarks, and networking platforms. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology. In this role, you will help drive the design, development, optimization, and bring-up of networking software and system technologies for AMD Helios rack-scale deployments, with a strong focus on both scale-up and scale-out networking. You will work across hardware, firmware, systems software, and architecture teams to enable high-performance, low-latency, and resilient networking solutions for next-generation AI infrastructure. THE PERSON: The ideal candidate should be passionate about software engineering and be able to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD. The ideal candidate is also deeply interested in distributed systems, datacenter networking, and rack-scale architecture, with strong hands-on experience in performance analysis, system bring-up, and cross-functional debugging. You should be comfortable working in ambiguous, fast-moving environments and be motivated by solving complex end-to-end system challenges spanning silicon, platform, and software layers.

Requirements

Strong object-oriented programming background, C/C++ preferred
Ability to write high quality code with a keen attention to detail
Experience with modern concurrent programming and threading APIs
Experience with Windows, Linux and/or Android operating system development
Experience with software development processes and tools such as debuggers and source code control systems (GitHub) is a plus
Effective communication and problem-solving skills
Strong experience in Linux systems software and networking stack development
Experience with datacenter networking, distributed systems, or high-performance interconnect technologies
Familiarity with scale-up and scale-out architectures in AI or large distributed computing environments
Experience with network protocols and communication stacks such as Ethernet, RDMA, RoCE, InfiniBand, TCP/IP, or related high-performance transport technologies
Experience debugging complex multi-node system issues involving hardware, firmware, drivers, and application workloads
Understanding of performance analysis methodologies for latency-sensitive and bandwidth-intensive applications
Experience with profiling, tracing, and observability tools used for system and network performance tuning

Nice To Haves

Familiarity with collective communication libraries, distributed runtimes, or workload orchestration environments is a plus
Experience with ASIC, NIC, switch, or platform bring-up is highly desirable
Knowledge of reliability, availability, and serviceability considerations in rack-scale or datacenter deployments is a plus
Ability to work effectively across architecture, hardware, firmware, software, and validation teams

Responsibilities

Work with AMD’s architecture specialists to improve future products
Apply a data minded approach to target optimization efforts
Stay informed of software and hardware trends and innovations, especially pertaining to algorithms and architecture
Design and develop new groundbreaking AMD technologies
Participating in new ASIC and hardware bring ups
Debugging/fix existing issues and research alternative, more efficient ways to accomplish the same work
Develop technical relationships with peers and partners
Design, develop, and optimize networking software for AMD Helios rack-scale systems
Enable and improve scale-up and scale-out networking performance for AI workloads
Collaborate with silicon, platform, firmware, driver, and systems teams to support new interconnect and networking features from concept through production
Drive hardware and software bring-up for networking subsystems, including link initialization, topology validation, performance tuning, and reliability testing
Analyze end-to-end network performance, latency, bandwidth utilization, congestion behavior, and communication efficiency across multi-node and rack-scale deployments
Develop tools, diagnostics, and telemetry frameworks to monitor network health, identify bottlenecks, and accelerate root cause analysis
Investigate and resolve issues across the stack, including NICs, switches, fabrics, transport layers, drivers, collectives libraries, and distributed runtime environments
Contribute to networking features that improve resiliency, scalability, serviceability, and deployment readiness in large-scale clusters
Partner with internal and external teams to validate interoperability and optimize AI workload performance on AMD platforms
Support performance characterization of communication libraries, collective operations, and distributed training or inference workloads over scale-up and scale-out fabrics
Help define software requirements and influence future hardware and system architecture for rack-scale networking solutions