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Senior Software Architect, AI Networking
On-siteFull-timeSoftware ArchitectureElectronics ManufacturingArtificial Intelligence
Lead research and development of end-to-end networking architectures for distributed AI training and inference. The role combines software and hardware expertise to optimize large-scale GPU systems and turn research into production networking features.
Responsibilities
- Lead research and development of networking solutions for distributed AI training and inference at scale
- Optimize job completion time, failure resilience, telemetry, scheduling, and workload placement
- Analyze existing deployments, build prototypes, and recommend architectural improvements
- Research emerging networking techniques and technologies
- Design, simulate, and validate scalable systems with network simulation tools
- Develop and test prototypes on large GPU clusters
- Collaborate with hardware, firmware, and software teams to convert research into networking product features
- Publish patents and present research at leading conferences
Requirements
- Master’s degree or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field; a bachelor’s degree with research experience and publications may also be considered
- At least 5 years of relevant experience
- Deep knowledge of networking and communication internals, including NCCL, RDMA, congestion control, and routing
- Strong software engineering skills in C++ and/or Python
- Strong system-level design and problem-solving abilities
- Excellent communication and collaboration skills across technical domains
Nice to have
- Publications at leading technical conferences
- Experience designing and building large-scale AI training clusters
- Postdoctoral research experience
- Practical knowledge of deep learning systems, GPU acceleration, and AI model execution flows
- Passion for solving complex technical problems and delivering impactful solutions